@proceedings {989, title = {Impact of free-water correction on white matter changes measured by diffusion tensor imaging in migraine}, volume = {4601}, year = {2023}, month = {2023}, abstract = {

Menstrual migraine affects about 25\% of female migraine patients. However, the diagnosis of migraine is particularly difficult because the brain changes associated with migraine are challenging to detect with imaging techniques. Diffusion-weighted MRI (dMRI) permits the detection of alterations in the microenvironment of the brain tissues. We investigate whether removing the contribution of the free water component from the diffusion-signal can provide increased sensitivity to identify white matter changes in migraine using diffusion tensor metrics.

}, author = {Guadilla, Irene and Fouto, Ana and {\'A}lvaro Planchuelo-G{\'o}mez and Trist{\'a}n-Vega, Antonio and Ruiz-Tagle, Amparo and Esteves, In{\^e}s and Caetano, Gina and Silva, Nuno and Vilela, Pedro and Gil-Gouveia, Raquel and Aja-Fern{\'a}ndez, Santiago and Figueiredo, Patr{\'\i}cia and Nunes, Rita} } @proceedings {985, title = {Validation of Deep Learning techniques for quality augmentation in diffusion MRI for clinical studies}, volume = {2786}, year = {2023}, month = {2023}, abstract = {

This work gathers the results of the QuadD22 challenge, held in MICCAI 2022. We evaluate whether Deep Learning (DL) Techniques are able to improve the quality of diffusion MRI data in clinical studies. To that end, we focused on a real study on migraine, where the differences between groups are drastically reduced when using 21 gradient directions instead of 61. Thus, we asked the participants to augment dMRI data acquired with only 21 directions to 61 via DL. The results were evaluated using a real clinical study with TBSS in which we statistically compared episodic migraine to chronic migraine.

}, author = {Aja-Fernandez, Santiago and Martin-Martin, Carmen and Pieciak, Tomasz and {\'A}lvaro Planchuelo-G{\'o}mez and Faiyaz, Abrar and Uddin, Nasir and Tiwari, Abhishek and Shigwan, Saurabh J and Zheng, Tianshu and Cao, Zuozhen and Blumberg, Stefano B and Sen, Snigdha and Yigit Avci, Mehmet and Li, Zihan and Wang, Xinyi and Tang, Zihao and Rauland, Amelie and Merhof, Dorit and Manzano Maria, Renata and Campos, Vinicius P and HashemiazadehKolowri, SeyyedKazem and DiBella, Edward and Peng, Chenxu and Chen, Zan and Ullah, Irfan and Mani, Merry and Eckstrom, Samuel and Baete, Steven H and Scifitto, Scifitto and Singh, Rajeev Kumar and Wu, Dan and Goodwin-Allcock, Tobias and Slator, Paddy J and Bilgic, Berkin and Tian, Qiyuan and Cabezas, Mariano and Santini, Tales and Andrade da Costa Vieira, Marcelo and Shen, Zhimin and Abdolmotalleby, Hesam and Filipiak, Patryk and Tristan-Vega, Antonio and de Luis-Garcia, Rodrigo} } @article {995, title = {Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies}, journal = {NeuroImage: Clinical}, volume = {39}, year = {2023}, pages = {103483}, abstract = {

The objective of this study is to evaluate the efficacy of deep learning (DL) techniques in improving the quality of diffusion MRI (dMRI) data in clinical applications. The study aims to determine whether the use of artificial intelligence (AI) methods in medical images may result in the loss of critical clinical information and/or the appearance of false information. To assess this, the focus was on the angular resolution of dMRI and a clinical trial was conducted on migraine, specifically between episodic and chronic migraine patients. The number of gradient directions had an impact on white matter analysis results, with statistically significant differences between groups being drastically reduced when using 21 gradient directions instead of the original 61. Fourteen teams from different institutions were tasked to use DL to enhance three diffusion metrics (FA, AD and MD) calculated from data acquired with 21 gradient directions and a b-value of 1000 s/mm2. The goal was to produce results that were comparable to those calculated from 61 gradient directions. The results were evaluated using both standard image quality metrics and Tract-Based Spatial Statistics (TBSS) to compare episodic and chronic migraine patients. The study results suggest that while most DL techniques improved the ability to detect statistical differences between groups, they also led to an increase in false positive. The results showed that there was a constant growth rate of false positives linearly proportional to the new true positives, which highlights the risk of generalization of AI-based tasks when assessing diverse clinical cohorts and training using data from a single group. The methods also showed divergent performance when replicating the original distribution of the data and some exhibited significant bias. In conclusion, extreme caution should be exercised when using AI methods for harmonization or synthesis in clinical studies when processing heterogeneous data in clinical studies, as important information may be altered, even when global metrics such as structural similarity or peak signal-to-noise ratio appear to suggest otherwise.

}, keywords = {Angular resolution, Artificial Intelligence, Deep learning, Diffusion tensor, diffusion MRI, machine learning}, issn = {2213-1582}, doi = {https://doi.org/10.1016/j.nicl.2023.103483}, url = {https://www.sciencedirect.com/science/article/pii/S2213158223001742}, author = {Santiago Aja-Fern{\'a}ndez and Carmen Mart{\'\i}n-Mart{\'\i}n and {\'A}lvaro Planchuelo-G{\'o}mez and Abrar Faiyaz and Md Nasir Uddin and Giovanni Schifitto and Abhishek Tiwari and Saurabh J. Shigwan and Rajeev Kumar Singh and Tianshu Zheng and Zuozhen Cao and Dan Wu and Stefano B. Blumberg and Snigdha Sen and Tobias Goodwin-Allcock and Paddy J. Slator and Mehmet Yigit Avci and Zihan Li and Berkin Bilgic and Qiyuan Tian and Xinyi Wang and Zihao Tang and Mariano Cabezas and Amelie Rauland and Dorit Merhof and Renata Manzano Maria and Vin{\'\i}cius Paran{\'\i}ba Campos and Tales Santini and Marcelo Andrade da Costa Vieira and SeyyedKazem HashemizadehKolowri and Edward DiBella and Chenxu Peng and Zhimin Shen and Zan Chen and Irfan Ullah and Merry Mani and Hesam Abdolmotalleby and Samuel Eckstrom and Steven H. Baete and Patryk Filipiak and Tanxin Dong and Qiuyun Fan and Rodrigo de Luis-Garc{\'\i}a and Antonio Trist{\'a}n-Vega and Tomasz Pieciak} } @conference {968, title = {Long-term grey matter structural changes in the transition from chronic migraine to episodic migraine}, booktitle = {8th Congress of the European Academy of Neurology}, year = {2022}, month = {2022}, abstract = {

Background and aims: The objective was to assess grey matter longitudinal changes in patients with chronic migraine (CM) who reverse to episodic migraine (EM) compared to those who do not reverse.

Methods: High-resolution 3D brain T1-weighted Magnetic Resonance Imaging data were obtained twice from migraine patients. The first acquisition was performed immediately after the first visit to the Headache Unit, before taking preventive treatments. The second timepoint was at least three years after the first acquisition. From the longitudinal pipeline of FreeSurfer (v6.0), the mean values of cortical thickness, surface area and grey matter volume of 68 cortical, 14 subcortical regions and the cerebellum were extracted. Longitudinal changes between patients with CM and those who reversed to EM were assessed with linear
mixed-effects models, setting p\<0.05 (false discovery rate corrected) as threshold for statistical significance.

Results: 22 patients were included, and 10 of them (45.5\%) reversed to EM. No statistically significant differences of age (42.0+-9.0 years) and sex (21 women, 95.5\%) were found between patient groups. Higher statistically significant values of the three parameters in patients who reversed to EM were found in the pericalcarine, parietal, orbitofrontal cortex, and amygdala (Table 1, Figure 1). In contrast, lower values were detected in the cingulum, caudal middle frontal cortex, cerebellum, caudate nucleus and pallidum (Figure 2). In the insula, higher thickness but lower area was appreciated in patients who reversed.

Conclusion: Patients with CM who reverse to EM present distinct patterns of increased and decreased morphometric parameters propagated in the orbital frontal cortex and the cingulum, respectively.

Disclosure: Nothing to disclose.

}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Marchante-Re{\'\i}llo, Ginebra and Sierra, {\'A}lvaro and Garc{\'\i}a-Azor{\'\i}n, David and Mart{\'\i}n-Mart{\'\i}n, Carmen and de Luis-Garc{\'\i}a, Rodrigo and Aja-Fern{\'a}ndez, Santiago and Moro, Ra{\'u}l and Rodr{\'\i}guez, Margarita and Gonz{\'a}lez-Osorio, Y{\'e}sica and {\'A}ngel L. Guerrero} } @conference {967, title = {Objective measurement of pain related to cardiac surgery: a study using algometry}, booktitle = {8th Congress of the European Academy of Neurology}, year = {2022}, month = {2022}, abstract = {

Background and aims: Algometry is a safe and objective technique to quantify pain, up to now used in headache research, but to a lesser extent to assess pain related to surgery. We aimed to analyze the demographic characteristics of pain related to cardiac surgery, assessed using static algometry.

Methods: Adult patients consecutively undergoing cardiac surgery were prospectively recruited. Pressure pain thresholds (PPT) were measured in both sides of sternum manubrium, body (five measures) and xiphoid process, preoperatively and on days 1, 3 and 7 postoperatively. Linear mixed-effects models were employed to assess the longitudinal changes and results were corrected for multiple comparisons following a false discovery rate procedure.

Results: We included 70 patients (41.4\% female) with a median age of 67.5 years (range 26-85). Regarding the baseline values, PPT were significantly lower in women and patients older than 65 years. After the surgery, there was a significant reduction of PPT in all assessed regions, which was partially compensated after seven days. Moreover, postoperatively, differences associated with age disappeared and those associated with sex were almost negligible. These differences related to age and sex increased after seven days of surgery, but this difference was lower in comparison with the baseline situation (Table 1, Figure 1). Postoperative pain perception was significantly higher (lower PPT) in both sexes.

Conclusion: Pain related to cardiac surgery can be measured with algometry, mainly during first postoperative days. Differences in pain sensitivity related to age and sex decrease after surgery.

Disclosure: No conflict of interest.

}, author = {Segura-M{\'e}ndez, B{\'a}rbara and {\'A}lvaro Planchuelo-G{\'o}mez and Sierra, {\'A}lvaro and Garc{\'\i}a-Azor{\'\i}n, David and Velasco-Garc{\'\i}a, E. and Fuentes-Mart{\'\i}n, {\'A}. and S{\'a}nchez, C. and V{\'a}zquez-Alarc{\'o}n de la Lastra, I. and {\'A}ngel L. Guerrero and Carrascal, Yolanda} } @conference {941, title = {Clinical course of migraine during the COVID-19 Lockdown}, booktitle = {International Headache Congress 2021}, year = {2021}, month = {2021}, publisher = {International Headache Society \& European Headache Federation}, organization = {International Headache Society \& European Headache Federation}, address = {Virtual Congress}, abstract = {

Objective: Previous studies have demonstrated that migraine can worsen due to stress, changes in lifestyle habits or infections. We hypothesize that changes during coronavirus disease 2019 (COVID-19) lockdown might have worsened the clinical course of migraine.
Methods: Retrospective survey study collecting demographic data, clinical variables related to headache (frequency), migraine (subjective worsening, frequency, and intensity), lockdown, and symptoms of post-traumatic stress from migraine patients followed-up at three Headache Units between June-July 2020.
Results: 222 subjects were included. Among them, 201/222 (90.5\%) were women, aged 42.5 +- 12.0 (mean +- SD). Subjective improvement of migraine was reported in 31/222 participants (14.0\%), while worsening in 105/222 (47.3\%) and was associated with changes in migraine triggers such as stress related to going outdoors and intake of specific foods/drinks. Intensity of attacks increased in 67/222 patients (30.2\%), and it was associated with the subjective worsening, female sex, recent insomnia, and use of acute medication during a headache. An increase in monthly days with any headache was observed in 105/222 patients (47.3\%) and was related to symptoms of post-traumatic stress, older age and living with five or more people.

Conclusion: Approximately half the migraine patients reported worsening of their usual pain during the lockdown; worsening was related to changes in triggers and the emotional impact of the lockdown.

}, url = {https://journals.sagepub.com/doi/pdf/10.1177/03331024211034005}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and {\'A}ngel L. Guerrero and Garc{\'\i}a-Azor{\'\i}n, David and Santos-Lasaosa, Sonia and P{\'e}rez-Navarro, Mar{\'\i}a P and Odriozola-Gonz{\'a}lez, Paula and Irurtia, Mar{\'\i}a Jes{\'u}s and Quintas, Sonia and Rodrigo de Luis-Garc{\'\i}a and Ana B Gago-Veiga} } @article {925, title = {A Clinically Viable Vendor-Independent and Device-Agnostic Solution for Accelerated Cardiac MRI Reconstruction}, journal = {Computer Methods and Programs in Biomedicine}, volume = {207}, year = {2021}, chapter = {106143}, issn = {0169-2607}, doi = {https://doi.org/10.1016/j.cmpb.2021.106143}, url = {https://www.sciencedirect.com/science/article/pii/S0169260721002182}, author = {Mart{\'\i}n-Gonz{\'a}lez, Elena and Elisa Moya-S{\'a}ez and Mench{\'o}n-Lara, Rosa-Mar{\'\i}a and J Royuela-del-Val and Palencia-de-Lara, C{\'e}sar and M. Rodr{\'\i}guez-Cayetano and Simmross-Wattenberg, Federico and Carlos Alberola-Lopez} } @article {952, title = {Effects of the onabotulinumtoxinA follow-up delay in migraine course during the COVID-19 lockdown}, journal = {Neurological Sciences}, volume = {42}, year = {2021}, pages = {5087-5092}, issn = {1590-3478}, doi = {10.1007/s10072-021-05180-8}, url = {https://doi.org/10.1007/s10072-021-05180-8}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and {\'A}ngel L. Guerrero and Garc{\'\i}a-Azor{\'\i}n, David and Santos-Lasaosa, Sonia and Navarro-P{\'e}rez, Mar{\'\i}a Pilar and Odriozola-Gonz{\'a}lez, Paula and Irurtia, Mar{\'\i}a Jes{\'u}s and Quintas, Sonia and de Luis-Garc{\'\i}a, Rodrigo and Ana B Gago-Veiga} } @article {944, title = {Evaluation of the Impact of the COVID-19 Lockdown in the Clinical Course of Migraine}, journal = {Pain Medicine}, volume = {22}, year = {2021}, month = {2021}, pages = {2079-2091}, abstract = {

Objective: Previous studies have demonstrated that emotional stress, changes in lifestyle habits and infections can worsen the clinical course of migraine. We hypothesize that changes in habits and medical care during coronavirus disease 2019 (COVID-19) lockdown might have worsened the clinical course of migraine.

Design: Retrospective survey study collecting online responses from migraine patients followed-up by neurologists at three tertiary hospitals between June and July 2020.

Methods: We used a web-based survey that included demographic data, clinical variables related with any headache (frequency) and migraine (subjective worsening, frequency, and intensity), lockdown, and symptoms of post-traumatic stress.

Results: The response rate of the survey was 239/324 (73.8\%). The final analysis included 222 subjects. Among them, 201/222 (90.5\%) were women, aged 42.5 +- 12.0 (mean+-SD). Subjective improvement of migraine during lockdown was reported in 31/222 participants (14.0\%), while worsening in 105/222 (47.3\%) and was associated with changes in migraine triggers such as stress related to going outdoors and intake of specific foods or drinks. Intensity of attacks increased in 67/222 patients (30.2\%), and it was associated with the subjective worsening, female sex, recent insomnia, and use of acute medication during a headache. An increase in monthly days with any headache was observed in 105/222 patients (47.3\%) and was related to symptoms of post-traumatic stress, older age and living with five or more people.

Conclusions: Approximately half the migraine patients reported worsening of their usual pain during the lockdown. Worse clinical course in migraine patients was related to changes in triggers and the emotional impact of the lockdown.

}, keywords = {COVID-19, Headache, Lockdown, Migraine, SARS-CoV-2}, issn = {1526-4637}, doi = {10.1093/pm/pnaa449}, url = {https://doi.org/10.1093/pm/pnaa449}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and {\'A}ngel L. Guerrero and Garc{\'\i}a-Azor{\'\i}n, David and Santos-Lasaosa, Sonia and Navarro-P{\'e}rez, Mar{\'\i}a Pilar and Odriozola-Gonz{\'a}lez, Paula and Irurtia, Mar{\'\i}a Jes{\'u}s and Quintas, Sonia and Rodrigo de Luis-Garc{\'\i}a and Ana B Gago-Veiga} } @conference {940, title = {Evaluation of the burden of migraine on the partners lifestyle: a multicenter study}, booktitle = {International Headache Congress 2021}, year = {2021}, month = {2021}, publisher = {International Headache Society \& European Headache Federation}, organization = {International Headache Society \& European Headache Federation}, address = {Virtual Congress}, abstract = {

Objective: Migraine is a highly disabling disease that affects the patient{\textquoteright}s life, but its consequences on the patient{\textquoteright}s partner have been barely studied. The objective was to analyze these effects on romantic relationship, relationship with their children, friendship and work; as well as to evaluate caregiver burden and the presence of anxiety and/or depression.
Methods: Cross-sectional observational study. An online survey was filled by partners of migraine patients from five Spanish Headache Units. Questions about the four assessed areas and two scales to evaluate anxiety, depression and caregiver burden (Hospital Anxiety and Depression Scale and Zarit scale) were included. The presence of anxiety and depression was compared to the Spanish prevalence (6.7\% in both cases).
Results: Out of 176 registered responses, 155 were accepted. The sample included 86.5\% of women, with mean age 44.2 +- 10.4 years. Effects on partners were found on love relationship and items concerning children and friendships, with a minor impact at work. Partners showed a significant moderate burden according to the Zarit scale (p = 12/155 = 0.077 [0.041-0.131]; p \< 0.001) and a higher anxiety rate than the 6.7\% national prevalence (p = 23/155 = 0.148 [0.096-0.214]; p \< 0.001), but similar depression rate.
Conclusion: We found an impact on the patient{\textquoteright}s partners on the studied areas. Migraine is a disease that implies caregiver burden in the patient{\textquoteright}s environment with possible effect on anxiety levels.

}, url = {https://journals.sagepub.com/doi/pdf/10.1177/03331024211034005}, author = {Fern{\'a}ndez-Bermejo, Eva M and {\'A}lvaro Planchuelo-G{\'o}mez and Quintas, Sonia and Gonzalez-Martinez, Alicia and Garc{\'\i}a-Azor{\'\i}n, David and Sierra, {\'A}lvaro and {\'A}ngel L. Guerrero and Santos-Lasaosa, Sonia and Navarro-P{\'e}rez, Mar{\'\i}a P and Gonz{\'a}lez-Garc{\'\i}a, Nuria and D{\'\i}az-de-Ter{\'a}n, Javier and Ana B Gago-Veiga} } @article {960, title = {Fast 4D elastic group-wise image registration. Convolutional interpolation revisited}, journal = {Computer Methods and Programs in Biomedicine}, volume = {200}, year = {2021}, pages = {105812}, abstract = {

Background and Objective:This paper proposes a new and highly efficient implementation of 3D+t groupwise registration based on the free-form deformation paradigm. Methods:Deformation is posed as a cascade of 1D convolutions, achieving great reduction in execution time for evaluation of transformations and gradients. Results:The proposed method has been applied to 4D cardiac MRI and 4D thoracic CT monomodal datasets. Results show an average runtime reduction above 90\%, both in CPU and GPU executions, compared with the classical tensor product formulation. Conclusions:Our implementation, although fully developed for the metric sum of squared differences, can be extended to other metrics and its adaptation to multiresolution strategies is straightforward. Therefore, it can be extremely useful to speed up image registration procedures in different applications where high dimensional data are involved.

}, keywords = {B-splines, Convolution, Efficient implementation, Free-form deformation, Groupwise Registration, Non-rigid registration}, issn = {0169-2607}, doi = {https://doi.org/10.1016/j.cmpb.2020.105812}, url = {https://www.sciencedirect.com/science/article/pii/S016926072031645X}, author = {Rosa-Mar{\'\i}a Mench{\'o}n-Lara and Javier Royuela-del-Val and Federico Simmross-Wattenberg and Pablo Casaseca-de-la-Higuera and Marcos Mart{\'\i}n-Fern{\'a}ndez and Carlos Alberola-L{\'o}pez} } @conference {942, title = {Has onabotulinumtoxinA follow-up delay during COVID-19 lockdown affected the migraine course?}, booktitle = {International Headache Congress 2021}, year = {2021}, month = {2021}, publisher = {International Headache Society \& European Headache Federation}, organization = {International Headache Society \& European Headache Federation}, address = {Virtual Congress}, abstract = {

Objective: During the COVID-19 pandemic face-to-face procedures have been postponed. We aim to evaluate the impact of onabotulinumtoxinA follow-up delay in migraine during COVID-19 pandemic.
Methods: Subjective worsening, intensity of migraine attacks and frequency of headache and migraine were retrospectively compared between patients with unmodified and interrupted onabotulinumtoxinA follow-up in Headache Units.
Results: We included 67 patients with chronic migraine or high-frequency episodic migraine under onabotulinumtoxinA treatment, 65 (97.0\%) female,
44.5 +- 12.1 years old. Treatment administration was voluntarily delayed in 14 (20.9\%) patients and nine (13.4\%) were unable to continue follow-up. Patients with uninterrupted follow-up during lockdown presented 8.4 and 8.1 less monthly days with headache (adjusted p = 0.011) and migraine attacks (adjusted p = 0.009) compared to patients whose follow-up was interrupted, respectively.
Conclusion: Involuntary delay of onabotulinumtoxinA follow-up in patients with migraine due to COVID-19 pandemic was associated with a higher frequency of headache and migraine attacks. Safe administration of onabotulinumtoxinA during lockdown should be promoted.

}, url = {https://journals.sagepub.com/doi/pdf/10.1177/03331024211034005}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and {\'A}ngel L. Guerrero and Garc{\'\i}a-Azor{\'\i}n, David and Santos-Lasaosa, Sonia and Navarro-P{\'e}rez, Mar{\'\i}a P and Odriozola-Gonz{\'a}lez, Paula and Irurtia, Mar{\'\i}a Jes{\'u}s and Quintas, Sonia and Rodrigo de Luis-Garc{\'\i}a and Ana B Gago-Veiga} } @article {923, title = {Neurobiological underpinnings of cognitive subtypes in psychoses: A cross-diagnostic cluster analysis}, journal = {Schizophrenia Research}, volume = {229}, year = {2021}, pages = {102-111}, abstract = {

Schizophrenia and bipolar disorder include patients with different characteristics, which may hamper the definition of biomarkers. One of the dimensions with greater heterogeneity among these patients is cognition. Recent studies support the identification of different patients{\textquoteright} subgroups along the cognitive domain using cluster analysis. Our aim was to validate clusters defined on the basis of patients{\textquoteright} cognitive status and to assess its relation with demographic, clinical and biological measurements. We hypothesized that subgroups characterized by different cognitive profiles would show differences in an array of biological data. Cognitive data from 198 patients (127 with chronic schizophrenia, 42 first episodes of schizophrenia and 29 bipolar patients) were analyzed by a K-means cluster approach and were compared on several clinical and biological variables. We also included 155 healthy controls for further comparisons. A two-cluster solution was selected, including a severely impaired group and a moderately impaired group. The severely impaired group was associated with higher illness duration and symptoms scores, lower thalamus and hippocampus volume, lower frontal connectivity and basal hypersynchrony in comparison to controls and the moderately impaired group. Moreover, both patients{\textquoteright} groups showed lower cortical thickness and smaller functional connectivity modulation than healthy controls. This study supports the existence of different cognitive subgroups within the psychoses with different neurobiological underpinnings.

}, keywords = {Cognition, Connectivity, Modulation, Volume, bipolar disorder, schizophrenia}, issn = {0920-9964}, doi = {https://doi.org/10.1016/j.schres.2020.11.013}, url = {https://www.sciencedirect.com/science/article/pii/S0920996420305521}, author = {Fern{\'a}ndez-Linsenbarth, In{\'e}s and {\'A}lvaro Planchuelo-G{\'o}mez and D{\'\i}ez, {\'A}lvaro and Arjona-Valladares, Antonio and Rodrigo de Luis-Garc{\'\i}a and Mart{\'\i}n-Santiago, {\'O}scar and Benito-S{\'a}nchez, Jos{\'e} Antonio and P{\'e}rez-Laureano, {\'A}ngela and Gonz{\'a}lez-Parra, David and Montes-Gonzalo, Carmen and Melero-Lerma, Raquel and Fern{\'a}ndez Morante, Sonia and Sanz-Fuentenebro, Javier and G{\'o}mez-Pilar, Javier and N{\'u}{\~n}ez-Novo, Pablo and Molina, Vicente} } @article {909, title = {Real world effectiveness and tolerability of candesartan in the treatment of migraine: a retrospective cohort study}, journal = {Scientific Reports}, volume = {11}, year = {2021}, pages = {3846}, abstract = {

To date, two randomized, controlled studies support the use of candesartan for migraine prophylaxis but with limited external validity. We aim to evaluate the effectiveness and tolerability of candesartan in clinical practice and to explore predictors of patient response. Retrospective cohort study including all patients with migraine who received candesartan between April 2008-February 2019. The primary endpoint was the number of monthly headache days during weeks 8{\textendash}12 of treatment compared to baseline. Additionally, we evaluated the frequency during weeks 20{\textendash}24. We analysed the percentage of patients with 50\% and 75\% response rates and the retention rates after three and 6\ months of treatment. 120/4121 patients were eligible, aged 45.9 [11.5]; 100 (83.3\%) female. Eighty-four patients (70\%) had chronic migraine and 53 (42.7\%) had medication-overuse headache. The median number of prior prophylactics was 3 (Inter-quartile range 2{\textendash}5). At baseline, patients had 20.5 {\textpm} 8.5 headache days per month, decreasing 4.3 {\textpm} 8.4\ days by 3\ months (weeks 12{\textendash}16) and by 4.7 {\textpm} 8.7\ days by 6\ months (paired Student{\textquoteright}s t-test, p \< 0.001). The percentage of patients with a 50\% response was 32.5\% at 3\ months and 31.7\% at 6\ months, while the retention rate was 85.0\% and 58.3\%. The number of prior treatments (Odds ratio 0.79, 95\% CI 0.64{\textendash}0.97) and the presence of daily headache (Odds ratio 0.39, 95\% CI 0.16{\textendash}0.97) were associated with a lower probability of response. Candesartan showed beneficial effects in the preventive treatment of migraine in clinical practice, including patients with chronic migraine, medication-overuse headache and resistance to prior prophylactics.

}, issn = {2045-2322}, doi = {10.1038/s41598-021-83508-2}, url = {https://doi.org/10.1038/s41598-021-83508-2}, author = {S{\'a}nchez-Rodr{\'\i}guez, Carmen and Sierra, {\'A}lvaro and {\'A}lvaro Planchuelo-G{\'o}mez and Mart{\'\i}nez-P{\'\i}as, Enrique and {\'A}ngel L. Guerrero and Garc{\'\i}a-Azor{\'\i}n, David} } @article {953, title = {Search for schizophrenia and bipolar biotypes using functional network properties}, journal = {Brain and Behavior}, volume = {11}, year = {2021}, pages = {e2415}, abstract = {

Introduction: Recent studies support the identification of valid subtypes within schizophrenia and bipolar disorder using cluster analysis. Our aim was to identify meaningful biotypes of psychosis based on network properties of the electroencephalogram. We hypothesized that these parameters would be more altered in a subgroup of patients also characterized by more severe deficits in other clinical, cognitive, and biological measurements.

Methods: A clustering analysis was performed using the electroencephalogram-based network parameters derived from graph-theory obtained during a P300 task of 137 schizophrenia (of them, 35 first episodes) and 46 bipolar patients. Both prestimulus and modulation of the electroencephalogram were included in the analysis. Demographic, clinical, cognitive, structural cerebral data, and the modulation of the spectral entropy of the electroencephalogram were compared between clusters. Data from 158 healthy controls were included for further comparisons.

Results: We identified two clusters of patients. One cluster presented higher prestimulus connectivity strength, clustering coefficient, path-length, and lower small-world index compared to controls. The modulation of clustering coefficient and path-length parameters was smaller in the former cluster, which also showed an altered structural connectivity network and a widespread cortical thinning. The other cluster of patients did not show significant differences with controls in the functional network properties. No significant differences were found between patients{\textasciiacute} clusters in first episodes and bipolar proportions, symptoms scores, cognitive performance, or spectral entropy modulation.

Conclusion: These data support the existence of a subgroup within psychosis with altered global properties of functional and structural connectivity.

}, keywords = {Biotypes, bipolar disorder, diffusion, electroencephalogram, network, schizophrenia}, doi = {https://doi.org/10.1002/brb3.2415}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/brb3.2415}, author = {Fern{\'a}ndez-Linsenbarth, In{\'e}s and {\'A}lvaro Planchuelo-G{\'o}mez and Be{\~n}o-Ruiz-de-la-Sierra, Rosa M. and D{\'\i}ez, Alvaro and Arjona, Antonio and P{\'e}rez, Adela and Rodr{\'\i}guez-Lorenzana, Alberto and del Valle, Pilar and de Luis-Garc{\'\i}a, Rodrigo and Mascialino, Guido and Holgado-Madera, Pedro and Segarra-Echevarr{\'\i}a, Rafael and Gomez-Pilar, Javier and N{\'u}{\~n}ez, Pablo and Bote-Boneaechea, Berta and Zambrana-G{\'o}mez, Antonio and Roig-Herrero, Alejandro and Molina, Vicente} } @article {951, title = {Time-efficient three-dimensional transmural scar assessment provides relevant substrate characterization for ventricular tachycardia features and long-term recurrences in ischemic cardiomyopathy}, journal = {Scientific Reports}, volume = {11}, year = {2021}, month = {2021}, url = {https://www.nature.com/articles/s41598-021-97399-w}, author = {S. Merino-Caviedes and Guti{\'e}rrez, L. and Alfonso-Almaz{\'a}n, J. and Santiago Sanz-Est{\'e}banez and Lucilio Cordero-Grande and Quintanilla, J. and S{\'a}nchez-Gonz{\'a}lez, J. and Marina-Breysse, M. and Gal{\'a}n-Arriola, C. and Enr{\'\i}quez-V{\'a}zquez, D. and Torres, C. and Pizarro, G. and Ib{\'a}{\~n}ez, B. and Peinado, R. and Merino, J. and P{\'e}rez-Villacast{\'\i}n, J. and Jalife. J and L{\'o}pez-Yunta, M. and V{\'a}zquez, M. and Aguado-Sierra, J. and Gonz{\'a}lez-Ferrer, J. and P{\'e}rez-Castellano, N. and Mart{\'\i}n-Fern{\'a}ndez, M. and Alberola-L{\'o}pez, C and Filgueiras-Rama, D.} } @article {912, title = {On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge}, journal = {bioRxiv}, year = {2021}, month = {2021}, doi = {10.1101/2021.03.02.433228}, url = {https://www.biorxiv.org/content/early/2021/03/02/2021.03.02.433228}, author = {De Luca, Alberto and Ianus, Andrada and Leemans, Alexander and Palombo, Marco and Shemesh, Noam and Zhang, Hui and Alexander, Daniel C and Nilsson, Markus and Froeling, Martijn and Biessels, Geert-Jan and Zucchelli, Mauro and Frigo, Matteo and Albay, Enes and Sedlar, Sara and Alimi, Abib and Deslauriers-Gauthier, Samuel and Deriche, Rachid and Fick, Rutger and Maryam Afzali and Tomasz Pieciak and Bogusz, Fabian and Santiago Aja-Fern{\'a}ndez and Ozarslan, Evren and Derek K. Jones and Chen, Haoze and Jin, Mingwu and Zhang, Zhijie and Wang, Fengxiang and Nath, Vishwesh and Parvathaneni, Prasanna and Morez, Jan and Sijbers, Jan and Jeurissen, Ben and Fadnavis, Shreyas and Endres, Stefan and Rokem, Ariel and Garyfallidis, Eleftherios and Sanchez, Irina and Prchkovska, Vesna and Rodrigues, Paulo and Landman, Bennet A and Schilling, Kurt G} } @article {933, title = {On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge}, journal = {NeuroImage}, year = {2021}, month = {2021}, pages = {118367}, issn = {1053-8119}, doi = {https://doi.org/10.1016/j.neuroimage.2021.118367}, url = {https://www.sciencedirect.com/science/article/pii/S1053811921006431}, author = {Alberto De Luca and Andrada Ianus and Alexander Leemans and Marco Palombo and Noam Shemesh and Hui Zhang and Daniel C. Alexander and Markus Nilsson and Martijn Froeling and Geert-Jan Biessels and Mauro Zucchelli and Matteo Frigo and Enes Albay and Sara Sedlar and Abib Alimi and Samuel Deslauriers-Gauthier and Rachid Deriche and Rutger Fick and Maryam Afzali and Tomasz Pieciak and Fabian Bogusz and Santiago Aja-Fern{\'a}ndez and Evren {\"O}zarslan and Derek K. Jones and Haoze Chen and Mingwu Jin and Zhijie Zhang and Fengxiang Wang and Vishwesh Nath and Prasanna Parvathaneni and Jan Morez and Jan Sijbers and Ben Jeurissen and Shreyas Fadnavis and Stefan Endres and Ariel Rokem and Eleftherios Garyfallidis and Irina Sanchez and Vesna Prchkovska and Paulo Rodrigues and Bennet A. Landman and Kurt G. Schilling} } @article {868, title = {Automatic non-destructive video estimation of maturation levels in Fuji apple (Malus Malus pumila) fruit in orchard based on colour (Vis) and spectral (NIR) data}, journal = {Biosystems Engineering}, volume = {195}, year = {2020}, pages = {136{\textendash}151}, abstract = {Non-destructive estimates information on the desired properties of fruit without damaging them. The objective of this work is to present an algorithm for the automatic and non-destructive estimation of four maturity stages (unripe, half-ripe, ripe, or overripe) of Fuji apples (Malus Malus pumila) using both colour and spectral data from fruit. In order to extract spectral and colour data to train a proposed system, 170 samples of Fuji apples were collected. Colour and spectral features were extracted using a CR-400 Chroma Meter colorimeter and a custom set up. The second component of colour space and near infrared (NIR) spectrum data in wavelength ranges of 535{\textendash}560 nm, 835{\textendash}855 nm, and 950{\textendash}975 nm, were used to train the proposed algorithm. A hybrid artificial neural network-simulated annealing algorithm (ANN-SA) was used for classification purposes. A total of 1000 iterations were conducted to evaluate the reliability of the classification process. Results demonstrated that after training the correction classification rate (CCR, accuracy) was, at the best state, 100\% (test set) using both colour and spectral data. The CCR of the four different classifiers were 93.27\%, 99.62\%, 98.55\%, and 99.59\%, for colour features, spectral data wavelength ranges of 535{\textendash}560 nm, 835{\textendash}855 nm, and 950{\textendash}975 nm, respectively, over the test set. These results suggest that the proposed method is capable of the non-destructive estimation of different maturity stages of Fuji apple with a remarkable accuracy, in particular within the 535{\textendash}560 nm wavelength range.}, doi = {https://doi.org/10.1016/j.biosystemseng.2020.04.015}, url = {https://www.sciencedirect.com/science/article/pii/S1537511020301148}, author = {Pourdarbani, Razieh and Sabzi, Sajad and Kalantari, Davood and Karimzadeh, Rouhollah and Ilbeygi, Elham and J I Arribas} } @article {864, title = {A Computer Vision System Based on Majority-Voting Ensemble Neural Network for the Automatic Classification of Three Chickpea Varieties}, journal = {Foods}, volume = {9}, year = {2020}, pages = {113}, abstract = {Since different varieties of crops have specific applications, it is therefore important to properly identify each cultivar, in order to avoid fake varieties being sold as genuine, i.e., fraud. Despite that properly trained human experts might accurately identify and classify crop varieties, computer vision systems are needed since conditions such as fatigue, reproducibility, and so on, can influence the expert{\textquoteright}s judgment and assessment. Chickpea (Cicer arietinum L.) is an important legume at the world-level and has several varieties. Three chickpea varieties with a rather similar visual appearance were studied here: Adel, Arman, and Azad chickpeas. The purpose of this paper is to present a computer vision system for the automatic classification of those chickpea varieties. First, segmentation was performed using an Hue Saturation Intensity (HSI) color space threshold. Next, color and textural (from the gray level co-occurrence matrix, GLCM) properties (features) were extracted from the chickpea sample images. Then, using the hybrid artificial neural network-cultural algorithm (ANN-CA), the sub-optimal combination of the five most effective properties (mean of the RGB color space components, mean of the HSI color space components, entropy of GLCM matrix at 90{\textdegree}, standard deviation of GLCM matrix at 0{\textdegree}, and mean third component in YCbCr color space) were selected as discriminant features. Finally, an ANN-PSO/ACO/HS majority voting (MV) ensemble methodology merging three different classifier outputs, namely the hybrid artificial neural network-particle swarm optimization (ANN-PSO), hybrid artificial neural network-ant colony optimization (ANN-ACO), and hybrid artificial neural network-harmonic search (ANN-HS), was used. Results showed that the ensemble ANN-PSO/ACO/HS-MV classifier approach reached an average classification accuracy of 99.10 {\textpm} 0.75\% over the test set, after averaging 1000 random iterations.}, doi = {https://doi.org/10.3390/foods9020113}, url = {https://www.mdpi.com/2304-8158/9/2/113}, author = {Pourdarbani, Razieh and Sabzi, Sajad and Kalantari, Davood and Hern{\'a}ndez-Hern{\'a}ndez, Jos{\'e} Luis and J I Arribas} } @article {865, title = {A Computer Vision System for the Automatic Classification of Five Varieties of Tree Leaf Images}, journal = {Computers}, volume = {9}, year = {2020}, pages = {6}, abstract = {A computer vision system for automatic recognition and classification of five varieties of plant leaves under controlled laboratory imaging conditions, comprising: 1{\textendash}Cydonia oblonga (quince), 2{\textendash}Eucalyptus camaldulensis dehn (river red gum), 3{\textendash}Malus pumila (apple), 4{\textendash}Pistacia atlantica (mt. Atlas mastic tree) and 5{\textendash}Prunus armeniaca (apricot), is proposed. 516 tree leaves images were taken and 285 features computed from each object including shape features, color features, texture features based on the gray level co-occurrence matrix, texture descriptors based on histogram and moment invariants. Seven discriminant features were selected and input for classification purposes using three classifiers: hybrid artificial neural network{\textendash}ant bee colony (ANN{\textendash}ABC), hybrid artificial neural network{\textendash}biogeography based optimization (ANN{\textendash}BBO) and Fisher linear discriminant analysis (LDA). Mean correct classification rates (CCR), resulted in 94.04\%, 89.23\%, and 93.99\%, for hybrid ANN{\textendash}ABC; hybrid ANN{\textendash}BBO; and LDA classifiers, respectively. Best classifier mean area under curve (AUC), mean sensitivity, and mean specificity, were computed for the five tree varieties under study, resulting in: 1{\textendash}Cydonia oblonga (quince) 0.991 (ANN{\textendash}ABC), 95.89\% (ANN{\textendash}ABC), 95.91\% (ANN{\textendash}ABC); 2{\textendash}Eucalyptus camaldulensis dehn (river red gum) 1.00 (LDA), 100\% (LDA), 100\% (LDA); 3{\textendash}Malus pumila (apple) 0.996 (LDA), 96.63\% (LDA), 94.99\% (LDA); 4{\textendash}Pistacia atlantica (mt. Atlas mastic tree) 0.979 (LDA), 91.71\% (LDA), 82.57\% (LDA); and 5{\textendash}Prunus armeniaca (apricot) 0.994 (LDA), 88.67\% (LDA), 94.65\% (LDA), respectively.}, doi = {https://doi.org/10.3390/computers9010006}, url = {https://www.mdpi.com/2073-431X/9/1/6}, author = {Sabzi, Sajad and Pourdarbani, Razieh and J I Arribas} } @article {887, title = {Factors associated with the presence of headache in hospitalized COVID-19 patients and impact on prognosis: a retrospective cohort study}, journal = {The Journal of Headache and Pain}, volume = {21}, year = {2020}, month = {Jul}, pages = {94}, abstract = {Headache is one of the most frequent neurologic manifestations in COVID-19. We aimed to analyze which symptoms and laboratory abnormalities were associated with the presence of headache and to evaluate if patients with headache had a higher adjusted in-hospital risk of mortality.}, issn = {1129-2377}, doi = {10.1186/s10194-020-01165-8}, url = {https://doi.org/10.1186/s10194-020-01165-8}, author = {Trigo, Javier and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}lvaro Planchuelo-G{\'o}mez and Mart{\'\i}nez-P{\'\i}as, Enrique and Talavera, Blanca and Hern{\'a}ndez-P{\'e}rez, Isabel and Valle-Pe{\~n}acoba, Gonzalo and Sim{\'o}n-Campo, Paula and de Lera, Mercedes and Chavarr{\'\i}a-Miranda, Alba and L{\'o}pez-Sanz, Cristina and Guti{\'e}rrez-S{\'a}nchez, Mar{\'\i}a and Mart{\'\i}nez-Velasco, Elena and Pedraza, Mar{\'\i}a and Sierra, {\'A}lvaro and G{\'o}mez-Vicente, Beatriz and Juan F Arenillas and {\'A}ngel L. Guerrero} } @article {853, title = {Groupwise Non-Rigid Registration with Deep Learning: An Affordable Solution Applied to 2D Cardiac Cine MRI Reconstruction}, journal = {Entropy}, volume = {22}, year = {2020}, pages = {687}, doi = {https://doi.org/10.3390/e22060687}, url = {https://www.mdpi.com/1099-4300/22/6/687}, author = {Mart{\'\i}n-Gonz{\'a}lez, Elena and Sevilla, Teresa and Revilla-Orodea, Ana and Pablo Casaseca-de-la-Higuera and Alberola-L{\'o}pez, Carlos} } @article {869, title = {Non-destructive Estimation of Chlorophyll a Content in Red Delicious Apple Cultivar Based on Spectral and Color Data}, journal = {Journal of Agricultural Sciences}, volume = {26}, year = {2020}, pages = {339{\textendash}348}, abstract = {Non-destructive estimation of the chemical properties of fruit is an important goal of researchers in the food industry, since online operations, such as fruit packaging based on the amount of different chemical properties and determining different stages of handling, are done based on these estimations. In this study, chlorophyll a content in Red Delicious apple cultivar is predicted as a chemical property that is altered by apple ripening stage, using non-destructive spectral and color methods combined. Two artificial intelligence methods based on hybrid Multilayer Perceptron Neural Network - Artificial Bee Colony Algorithm (ANN-ABC) and Partial least squares regression (PLSR) were used in order to obtain a non-destructive estimation of chlorophyll a content. In application of the PLSR method, various pre-processing algorithms were used. In order to statistically properly validate the hybrid ANN-ABC predictive method, 20 runs were performed. Results showed that the best regression coefficient of the PLSR method in predicting chlorophyll a content using spectral data alone was 0.918. At the same time, the average determination coefficient over 20 repetitions in hybrid ANN-ABC in the estimation of chlorophyll a content, using spectral data and color features were higher than 0.92{\textpm}0.040 and 0.89{\textpm}0.045, respectively, which to our knowledge is a remarkable non-intrusive estimation result.}, doi = {https://doi.org/10.15832/ankutbd.523574}, url = {https://dergipark.org.tr/en/pub/ankutbd/issue/56429/523574}, author = {Yousef Abbaspour-Gilandeh and Sabzi, Sajad and Azadshahraki, Farzad and Karimzadeh, Rouhollah and Ilbeygi, Elham and J I Arribas} } @article {870, title = {Non-destructive visible and short-wave near-infrared spectroscopic data estimation of various physicochemical properties of Fuji apple (Malus pumila) fruits at different maturation stages}, journal = {Chemometrics and Intelligent Laboratory Systems}, year = {2020}, pages = {104147}, abstract = {measurement of physicochemical properties of fruits during maturation stages can help having proper fruit management. Spectroscopy data analyzing and processing is among the commonly used methods that enable non-destructive accurate property estimation. Non-destructive linear (partial least squares regression, PSLR) and non-linear (artificial neural network, ANN) regression estimation of different physicochemical properties including firmness, acidity (pH) and starch content of 160 Fuji (Malus pumila) apple fruit samples at various maturity stages using visible and short wave near infrared (VSWIR) spectroscopic data in wavelength range 400{\textendash}1000 nm is investigated with the following steps: (1) harvesting 160 Fuji apple samples at four different maturation levels; (2) extracting spectral data in wavelength range of 400{\textendash}1000 nm; extracting physicochemical properties of tissue firmness, acidity (pH) and starch content; (3) pre-processing the reflectance spectra from each sample; (4) selecting effective wavelength values for each chemical property; and (5) non-destructive estimation of tissue firmness, acidity (pH) and starch content using spectral data range 400{\textendash}1000 nm and spectral data based on effective wavelengths, by means of an ensemble average artificial neural network method. Results show that the neural ensemble reached similar results when using VSWIR spectral data content (wavelength range) and fixed effective selected NIR wavelengths. Correlation coefficients estimating tissue firmness, acidity (pH), and starch content were 0.800, 0.919, and 0.940 for VSWIR spectral data (linear PLS regression), 0.826, 0.947, and 0.969 for VSWIR spectral data (non-linear ANN), 0.827, 0.946, and 0.969 for fixed NIR effective wavelengths (non-linear ANN). Mean {\textpm} std. Regression coefficients for tissue firmness, acidity (pH), and starch content were 0.717 {\textpm} 0.113, 0.786 {\textpm} 0.131, and 0.941 {\textpm} 0.013 for Vis/NIR spectral data (linear PLS regression), 0.849 {\textpm} 0.017, 0.930 {\textpm} 0.017, and 0.967 {\textpm} 0.007 for Vis/NIR spectral data (non-linear ANN), 0.852 {\textpm} 0.016, 0.929 {\textpm} 0.015, and 0.966 {\textpm} 0.006 for fixed effective NIR wavelengths (non-linear ANN).}, doi = {https://doi.org/10.1016/j.chemolab.2020.104147}, url = {https://www.sciencedirect.com/science/article/pii/S016974392030304X}, author = {Pourdarbani, Razieh and Sabzi, Sajad and Kalantari, Davood and J I Arribas} } @article {san2020two, title = {Two-stage memetic algorithm for blind equalisation in direct-sequence/code-division multiple-access systems}, journal = {IET Communications}, year = {2020}, publisher = {IET Digital Library}, author = {San-Jos{\'e}-Revuelta, Luis M and Pablo Casaseca-de-la-Higuera} } @article {841, title = {A Web-Based Educational Magnetic Resonance Simulator: Design, Implementation and Testing}, journal = {Journal of Medical Systems}, volume = {44}, year = {2020}, month = {2020}, pages = {9}, author = {Trece{\~n}o-Fern{\'a}ndez, Daniel and Calabia-del-Campo, Juan and Bote-Lorenzo, Miguel L and S{\'a}nchez, Eduardo G{\'o}mez and Rodrigo de Luis-Garc{\'\i}a and Alberola-L{\'o}pez, Carlos} } @article {866, title = {Weed Classification for Site-Specific Weed Management Using an Automated Stereo Computer-Vision Machine-Learning System in Rice Fields}, journal = {Plants}, volume = {9}, year = {2020}, pages = {559}, abstract = {Site-specific weed management and selective application of herbicides as eco-friendly techniques are still challenging tasks to perform, especially for densely cultivated crops, such as rice. This study is aimed at developing a stereo vision system for distinguishing between rice plants and weeds and further discriminating two types of weeds in a rice field by using artificial neural networks (ANNs) and two metaheuristic algorithms. For this purpose, stereo videos were recorded across the rice field and different channels were extracted and decomposed into the constituent frames. Next, upon pre-processing and segmentation of the frames, green plants were extracted out of the background. For accurate discrimination of the rice and weeds, a total of 302 color, shape, and texture features were identified. Two metaheuristic algorithms, namely particle swarm optimization (PSO) and the bee algorithm (BA), were used to optimize the neural network for selecting the most effective features and classifying different types of weeds, respectively. Comparing the proposed classification method with the K-nearest neighbors (KNN) classifier, it was found that the proposed ANN-BA classifier reached accuracies of 88.74\% and 87.96\% for right and left channels, respectively, over the test set. Taking into account either the arithmetic or the geometric means as the basis, the accuracies were increased up to 92.02\% and 90.7\%, respectively, over the test set. On the other hand, the KNN suffered from more cases of misclassification, as compared to the proposed ANN-BA classifier, generating an overall accuracy of 76.62\% and 85.59\% for the classification of the right and left channel data, respectively, and 85.84\% and 84.07\% for the arithmetic and geometric mean values, respectively.}, doi = {https://doi.org/10.3390/plants9050559}, url = {https://www.mdpi.com/2223-7747/9/5/559}, author = {Dadashzadeh, Mojtaba and Yousef Abbaspour-Gilandeh and Mesri-Gundoshmian, Tarahom and Sabzi, Sajad and Hern{\'a}ndez-Hern{\'a}ndez, Jose Luis and Hern{\'a}ndez-Hern{\'a}ndez, Mario and J I Arribas} } @article {867, title = {An automatic visible-range video weed detection, segmentation and classification prototype in potato field}, journal = {Heliyon}, volume = {6}, year = {2020}, pages = {e03685}, abstract = {Weeds might be defined as destructive plants that grow and compete with agricultural crops in order to achieve water and nutrients. Uniform spray of herbicides is nowadays a common cause in crops poisoning, environment pollution and high cost of herbicide consumption. Site-specific spraying is a possible solution for the problems that occur with uniform spray in fields. For this reason, a machine vision prototype is proposed in this study based on video processing and meta-heuristic classifiers for online identification and classification of Marfona potato plant (Solanum tuberosum) and 4299 samples from five weed plant varieties: Malva neglecta (mallow), Portulaca oleracea (purslane), Chenopodium album L (lamb{\textquoteright}s quarters), Secale cereale L (rye) and Xanthium strumarium (coklebur). In order to properly train the machine vision system, various videos taken from two Marfona potato fields within a surface of six hectares are used. After extraction of texture features based on the gray level co-occurrence matrix (GLCM), color features, spectral descriptors of texture, moment invariants and shape features, six effective discriminant features were selected: the standard deviation of saturation (S) component in HSV color space, difference of first and seventh moment invariants, mean value of hue component (H) in HSI color space, area to length ratio, average blue-difference chrominance (Cb) component in YCbCr color space and standard deviation of in-phase (I) component in YIQ color space. Classification results show a high accuracy of 98\% correct classification rate (CCR) over the test set, being able to properly identify potato plant from previously mentioned five different weed varieties. Finally, the machine vision prototype was tested in field under real conditions and was able to properly detect, segment and classify weed from potato plant at a speed of up to 0.15 m/s.}, doi = {https://doi.org/10.1016/j.heliyon.2020.e03685}, url = {https://www.sciencedirect.com/science/article/pii/S2405844020305302}, author = {Sabzi, Sajad and Yousef Abbaspour-Gilandeh and J I Arribas} } @article {san2020new, title = {A new flower pollination algorithm for equalization in synchronous DS/CDMA multiuser communication systems}, journal = {Soft Computing}, year = {2020}, month = {2000}, pages = {1{\textendash}15}, publisher = {Springer Berlin Heidelberg}, author = {San-Jos{\'e}-Revuelta, Luis M and Pablo Casaseca-de-la-Higuera} } @article {863, title = {A three-variety automatic and non-intrusive computer vision system for the estimation of orange fruit pH value}, journal = {Measurement}, volume = {152}, year = {2020}, pages = {107298}, abstract = {An automatic 3-variety computer vision orange fruit pH value assessment system in the visible-range is presented, including each 100 different color images from Bam, Blood and Thomson orange of which the true pH has been measured and is known in advance. A total of 452 features are extracted from segmented orange color images. Results with repeated trials include: true versus estimated mean pH values, true minus estimated pH values boxplots, fitness regression dispersion plots and various error measure boxplots, for both single orange variety as well as the three-orange varieties altogether (test set), showing consistent results over all three orange varieties. Regression coefficient for pH estimation in Bam, Blood and Thomson orange varieties, were 0.950, 0.935 and 0.957, respectively. Results show that the hybrid ANN-ABC estimates pH values in orange quite similarly among orange varieties, implying that properly pH values estimation is possible for different orange varieties, regardless of orange type.}, doi = {https://doi.org/10.1016/j.measurement.2019.107298}, url = {https://www.sciencedirect.com/science/article/pii/S0263224119311625}, author = {Sabzi, Sajad and Javadikia, Hossein and J I Arribas} } @article {862, title = {An Automatic Non-Destructive Method for the Classification of the Ripeness Stage of Red Delicious Apples in Orchards Using Aerial Video}, journal = {Agronomy}, volume = {9}, year = {2019}, abstract = {The estimation of the ripening state in orchards helps improve post-harvest processes. Picking fruits based on their stage of maturity can reduce the cost of storage and increase market outcomes. Moreover, aerial images and the estimated ripeness can be used as indicators for detecting water stress and determining the water applied during irrigation. Additionally, they can also be related to the crop coefficient (Kc) of seasonal water needs. The purpose of this research is to develop a new computer vision algorithm to detect the existing fruits in aerial images of an apple cultivar (of Red Delicious variety) and estimate their ripeness stage among four possible classes: unripe, half-ripe, ripe, and overripe. The proposed method is based on a combination of the most effective color features and a classifier based on artificial neural networks optimized with genetic algorithms. The obtained results indicate an average classification accuracy of 97.88\%, over a dataset of 8390 images and 27,687 apples, and values of the area under the ROC (receiver operating characteristic) curve near or above 0.99 for all classes. We believe this is a remarkable performance that allows a proper non-intrusive estimation of ripening that will help to improve harvesting strategies.}, doi = {https://doi.org/10.3390/agronomy9020084}, url = {https://www.mdpi.com/2073-4395/9/2/84}, author = {S Sabzi and Yousef Abbaspour-Gilandeh and G Garcia-Mateos and A Ruiz-Canales and J M Molina-Martinez and J I Arribas} } @article {801, title = {A Machine Hearing System for Robust Cough Detection Based on a High-Level Representation of Band-Specific Audio Features}, journal = {IEEE Transactions on Biomedical Engineering}, volume = {66}, year = {2019}, pages = {2319-2330}, author = {Monge-Alvarez, Jesus and Hoyos-Barcelo, Carlos and San Jose-Revuelta, Luis M and Pablo Casaseca-de-la-Higuera} } @conference {jimenez2019novel, title = {A Novel Design Method for Digital FIR/IIR Filters Based on the Shuffle Frog-Leaping Algorithm}, booktitle = {2019 27th European Signal Processing Conference (EUSIPCO)}, year = {2019}, pages = {1{\textendash}5}, publisher = {IEEE}, organization = {IEEE}, author = {Jim{\'e}nez-Galindo, Daniel and Pablo Casaseca-de-la-Higuera and San-Jos{\'e}-Revuelta, Luis M} } @article {807, title = {OpenCLIPER: An OpenCL-Based C++ Framework for Overhead-Reduced Medical Image Processing and Reconstruction on Heterogeneous Devices}, journal = {IEEE Journal of Biomedical and Health Informatics}, volume = {23}, year = {2019}, month = {July}, pages = {1702-1709}, abstract = {

Medical image processing is often limited by the computational cost of the involved algorithms. Whereas dedicated computing devices (GPUs in particular) exist and do provide significant efficiency boosts, they have an extra cost of use in terms of housekeeping tasks (device selection and initialization, data streaming, synchronization with the CPU, and others), which may hinder developers from using them. This paper describes an OpenCL-based framework that is capable of handling dedicated computing devices seamlessly and that allows the developer to concentrate on image processing tasks. The framework handles automatically device discovery and initialization, data transfers to and from the device and the file system and kernel loading and compiling. Data structures need to be defined only once independently of the computing device; code is unique, consequently, for every device, including the host CPU. Pinned memory/buffer mapping is used to achieve maximum performance in data transfers. Code fragments included in the paper show how the computing device is almost immediately and effortlessly available to the users algorithms, so they can focus on productive work. Code required for device selection and initialization, data loading and streaming and kernel compilation is minimal and systematic. Algorithms can be thought of as mathematical operators (called processes), with input, output and parameters, and they may be chained one after another easily and efficiently. Also for efficiency, processes can have their initialization work split from their core workload, so process chains and loops do not incur in performance penalties. Algorithm code is independent of the device type targeted.

}, keywords = {C++, C++ languages, Data structures, GPU, Graphics processing units, Image reconstruction, Informatics, Kernel, Libraries, Medical imaging, OpenCL}, issn = {2168-2194}, doi = {10.1109/JBHI.2018.2869421}, author = {Federico Simmross-Wattenberg and M. Rodr{\'\i}guez-Cayetano and J Royuela-del-Val and E. Mart{\'\i}n-Gonz{\'a}lez and E. Moya-S{\'a}ez and M. Mart{\'\i}n-Fern{\'a}ndez and C. Alberola-L{\'o}pez} } @article {861, title = {An Outdoors Multi-stage Fruit-tree Orchard Video Image Segmentation System under Natural Conditions}, journal = {Journal of Agricultural Sciences}, volume = {25}, year = {2019}, chapter = {427}, abstract = {Segmentation is an important part of each machine vision system that has a direct relationship with the final system accuracy and performance. Outdoors segmentation is often complex and difficult due to both changes in sunlight intensity and the different nature of background objects. However, in fruit-tree orchards, an automatic segmentation algorithm with high accuracy and speed is very desirable. For this reason, a multi-stage segmentation algorithm is applied for the segmentation of apple fruits with Red Delicious cultivar in orchard under natural light and background conditions. This algorithm comprises a combination of five segmentation stages, based on: 1- L*u*v* color space, 2- local range texture feature, 3- intensity transformation, 4- morphological operations, and 5- RGB color space. To properly train a segmentation algorithm, several videos were recorded under nine different light intensities in Iran-Kermanshah (longitude: 7.03E; latitude: 4.22N) with natural (real) conditions in terms of both light and background. The order of segmentation stage methods in multi-stage algorithm is very important since has a direct relationship with final segmentation accuracy. The best order of segmentation methods resulted to be: 1- color, 2- texture and 3- intensity transformation methods. Results show that the values of sensitivity, accuracy and specificity, in both classes, were higher than 97.5\%, over the test set. We believe that those promising numbers imply that the proposed algorithm has a remarkable performance and could potentially be applied in real-world industrial case.}, doi = {https://doi.org/10.15832/ankutbd.434137}, url = {https://dergipark.org.tr/en/pub/ankutbd/issue/50426/434137}, author = {Yousef Abbaspour-Gilandeh and Sajad Sabzi and J I Arribas} } @article {menchon2019reconstruction, title = {Reconstruction techniques for cardiac cine MRI}, journal = {Insights into imaging}, volume = {10}, number = {1}, year = {2019}, pages = {100}, publisher = {Springer Berlin Heidelberg}, author = {Mench{\'o}n-Lara, Rosa-Mar{\'\i}a and Simmross-Wattenberg, Federico and Pablo Casaseca-de-la-Higuera and Mart{\'\i}n-Fern{\'a}ndez, Marcos and Alberola-L{\'o}pez, Carlos} } @conference {791, title = {On the Construction of Non Linear Adjoint Operators: Application to L1-Penalty Dynamic Image Reconstruction}, booktitle = {Congreso Anual de Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica (CASEIB)}, year = {2018}, month = {11/2018}, address = {Ciudad Real, Espa{\~n}a}, abstract = {

The purpose of this work is to develop a methodology for the adjoint operators application in non linear optimization problems. The use of adjoint operators is very popular for numerical control theory; one of its main applications is devised for image reconstruction. Most of these reconstruction techniques are limited to linear L1-constraints whose adjoints are well-defined. We aim to extend these image reconstruction techniques allowing the terms involved to be non linear. For these purpose, we have generalized the concept of adjoint operator under the basis of Taylor{\textquoteright}s formula, using Gateaux derivatives in order to construct a linearised adjoint operator associated to the non linear operator. The proposed approach has been validated in a Magnetic Resonance Imaging (MRI) reconstruction framework with Cartesian subsampled k-space data using Compressed Sensing based techniques and a groupwise registration algorithm for motion compensation.
The proposed algorithm has shown to be able to effectively deal with the presence of both physiological motion and subsampling artefacts, increasing accuracy and robustness of the reconstruction as compared with its linear counterpart.

}, author = {Santiago Sanz-Est{\'e}banez and Elisa Moya-S{\'a}ez and J Royuela-del-Val and Carlos Alberola-L{\'o}pez} } @article {799, title = {Efficient computation of image moments for robust cough detection using smartphones}, journal = {Computers in biology and medicine}, volume = {100}, year = {2018}, pages = {176{\textendash}185}, author = {Hoyos-Barcel{\'o}, Carlos and Monge-{\'A}lvarez, Jes{\'u}s and Pervez, Zeeshan and San-Jos{\'e}-Revuelta, Luis M and Pablo Casaseca-de-la-Higuera} } @article {771, title = {Efficient k-NN Implementation for Real-Time Detection of Cough Events in Smartphones}, journal = {IEEE Journal of Biomedical and Health Informatics}, volume = {23}, year = {2018}, pages = {1662-1671}, chapter = {1662}, author = {Hoyos-Barcel{\'o}, Carlos and Monge-{\'A}lvarez, Jes{\'u}s and Shakir, Muhammad Zeeshan and Jose-Maria Alcaraz-Calero and Pablo Casaseca-de-la-Higuera} } @article {733, title = {Joint Groupwise Registration and ADC Estimation in the Liver using a B-Value Weighted Metric}, journal = {Magnetic Resonance Imaging}, volume = {46}, year = {2018}, month = {2018}, pages = {1-8}, type = {Original Contribution}, chapter = {1}, abstract = {

The purpose of this work is to develop a groupwise elastic multimodal registration algorithm for robust ADC estimation in the liver on multiple breath hold diffusion weighted images.

We introduce a joint formulation to simultaneously solve both the registration and the estimation problems. In order to avoid non-reliable transformations and undesirable noise amplification, we have included appropriate smoothness constraints for both problems. Our metric incorporates the ADC estimation residuals, which are inversely weighted according to the signal content in each diffusion weighted image.

Results show that the joint formulation provides a statistically significant improvement in the accuracy of the ADC estimates. Reproducibility has also been measured on real data in terms of the distribution of ADC differences obtained from different\ b-values\ subsets.\ 

The proposed algorithm is able to effectively deal with both the presence of motion and the geometric distortions, increasing accuracy and reproducibility in diffusion parameters estimation.

}, keywords = {ADC Estimation, Diffusion Weighted Imaging, Groupwise Registration, Joint Optimization, Residual Minimization Metric}, doi = {https://doi.org/10.1016/j.mri.2017.10.002}, url = {http://www.sciencedirect.com/science/article/pii/S0730725X17302187}, author = {Santiago Sanz-Est{\'e}banez and I{\~n}aki Rabanillo-Viloria and J Royuela-del-Val and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @conference {784, title = {Joint Image Reconstruction and Phase Corruption Maps Estimation in Multi-Shot Echo Planar Imaging}, booktitle = {MICCAI}, year = {2018}, month = {09/2018}, publisher = {MICCAI}, organization = {MICCAI}, address = {Granada}, abstract = {

Multishot echo-planar imaging is a common strategy in diffusion Magnetic Resonance Imaging to reduce the artifacts caused by the long echo-trains in single-shot acquisitions. However, it su ers from shot-to-shot phase discrepancies associated to subject motion, which can notably degrade the quality of the reconstructed image. Consequently, some
type of motion-induced phases error correction needs to be incorporated into the reconstruction process. In this paper we focus on ridig motion induced errors, which have proved to corrupt the shots with linear phase maps. By incorporating this prior knowledge, we propose a maximum likelihood formulation that estimates both the parameters that characterize the linear phase maps and the reconstructed image. In order to make the problem tractable, we follow a greedy iterative procedure that alternates between the estimation of each of them. Simulation data are used to illustrate the performance of the method against state-of-the-art alternatives.

}, author = {I{\~n}aki Rabanillo-Viloria and Santiago Sanz-Est{\'e}banez and Santiago Aja-Fern{\'a}ndez and Joseph V. Hajnal and Carlos Alberola-L{\'o}pez and Lucilio Cordero-Grande} } @article {794, title = {Longitudinal Connectomes as a Candidate Progression Marker for Prodromal Parkinson{\textquoteright}s Disease}, journal = {Frontiers in Neuroscience}, volume = {12}, year = {2018}, pages = {967}, author = {{\'O}scar Pe{\~n}a-Nogales and Ellmore, Timothy Michael and Rodrigo de Luis-Garc{\'\i}a and Suescun, Jessika and Schiess, Mya Caryn and Giancardo, Luca} } @article {779, title = {Robust Estimation of the Apparent Diffusion Coefficient Invariant to Acquisition Noise and Physiological Motion}, journal = {Magnetic Resonance Imaging}, volume = {53}, year = {2018}, pages = {123-133}, abstract = {

In this work we have proposed a methodology for the estimation of the apparent diffusion coefficient in the body from multiple breath hold diffusion weighted images, which is robust to two preeminent confounding factors: noise and motion during acquisition. We have extended a method for the joint groupwise multimodal registration and apparent diffusion coefficient estimation, previously proposed by the authors, in order to correct the bias that arises from the non-Gaussianity of the data and the registration procedure. Results show that the proposed methodology provides a statistically significant improvement both in robustness for displacement fields calculation and in terms of accuracy for the apparent diffusion coefficient estimation as compared with traditional sequential approaches. Reproducibility has also been measured on real data in terms of the distribution of apparent diffusion coefficient differences obtained from different b-values subsets. Our proposal has shown to be able to effectively correct the estimation bias by introducing additional computationally light procedures to the original method, thus providing robust apparent diffusion coefficient maps in the liver and allowing an accurate and reproducible analysis of the tissue.

}, keywords = {Acquisition Noise, Apparent Diffusion Coefficient, Diffusion Weighted Imaging, Multimodal Groupwise Registration, Patient Movement Correction}, doi = {https://doi.org/10.1016/j.mri.2018.07.005}, url = {https://www.sciencedirect.com/science/article/pii/S0730725X18300687}, author = {Santiago Sanz-Est{\'e}banez and Tomasz Pieciak and Carlos Alberola-L{\'o}pez and Santiago Aja-Fern{\'a}ndez} } @conference {785, title = {Robust Windowed Harmonic Phase Analysis with a Single Acquisition}, booktitle = {MICCAI }, year = {2018}, month = {2018}, publisher = {MICCAI}, organization = {MICCAI}, address = {Granada}, abstract = {

The HARP methodology is a widely extended procedure for cardiac tagged magnetic resonance imaging since it is able to analyse local mechanical behaviour of the heart; extensions and improvements of this method have also been reported since HARP was released. Acquisition of an over-determined set of orientations is one of such alternatives,
which has notably increased HARP robustness at the price of increasing examination time. In this paper, we explore an alternative to this method based on the use of multiple peaks, as opposed to multiple orientations, intended for a single acquisition. Performance loss is explored with respect to multiple orientations in a real setting. In addition, we have assessed, by means of a computational phantom, optimal tag orientations and spacings of the stripe pattern by minimizing the Frobenius norm of the difference between the ground truth and the estimated material deformation gradient tensor. Results indicate that, for a single acquisition, multiple peaks as opposed to multiple orientations, are indeed preferable.

}, keywords = {Cardiac Tagged Magnetic Resonance Imaging, HARmonic Phase, Multi-Harmonic Analysis, Robust Strain Reconstruction}, author = {Santiago Sanz-Est{\'e}banez and Lucilio Cordero-Grande and Marcos Martin-Fern{\'a}ndez and Carlos Alberola L{\'o}pez} } @article {749, title = {Vortical Features for Myocardial Rotation Assessment in Hypertrophic Cardiomyopathy using Cardiac Tagged Magnetic Resonance}, journal = {Medical Image Analysis}, volume = {In Press}, year = {2018}, month = {04/2018}, type = {Original Article}, abstract = {

Left ventricular rotational motion is a feature of normal and diseased cardiac function. However, classical torsion and twist measures rely on the definition of a rotational axis which may not exist. This paper reviews global and local rotation descriptors of myocardial motion and introduces new curl-based (vortical) features built from tensorial magnitudes, intended to provide better comprehension about fibrotic tissue characteristics mechanical properties. Fifty-six cardiomyopathy patients and twenty-two healthy volunteers have been studied using tagged magnetic resonance by means of harmonic phase analysis. Rotation descriptors are built, with no assumption about a regular geometrical model, from different approaches. The extracted vortical features have been tested by means of a sequential cardiomyopathy classification procedure; they have proven useful for the regional characterization of the left ventricular function by showing great separability not only between pathologic and healthy patients but also, and specifically, between heterogeneous phenotypes within cardiomyopathies.

}, doi = {10.1016/j.media.2018.03.005}, author = {Santiago Sanz-Est{\'e}banez and Lucilio Cordero-Grande and T. Sevilla-Ruiz and A. Revilla-Orodea and Rodrigo de Luis-Garc{\'\i}a and M Martin-Fernandez and Carlos Alberola-Lopez} } @article {858, title = {An automatic and non-intrusive hybrid computer vision system for the estimation of peel thickness in Thomson orange}, journal = {Spanish Journal of Agricultural Research}, volume = {16}, year = {2018}, pages = {e0204}, abstract = {Orange peel has important flavor and nutrition properties and is often used for making jam and oil in the food industry. For previous reasons, oranges with high peel thickness are valuable. In order to properly estimate peel thickness in Thomson orange fruit, based on a number of relevant image features (area, eccentricity, perimeter, length/area, blue component, green component, red component, width, contrast, texture, width/area, width/length, roughness, and length) a novel automatic and non-intrusive approach based on computer vision with a hybrid particle swarm optimization (PSO), genetic algorithm (GA) and artificial neural network (ANN) system is proposed. Three features (width/area, width/length and length/area ratios) were selected as inputs to the system. A total of 100 oranges were used, performing cross validation with 100 repeated experiments with uniform random samples test sets. Taguchi{\textquoteright}s robust optimization technique was applied to determine the optimal set of parameters. Prediction results for orange peel thickness (mm) based on the levels that were achieved by Taguchi{\textquoteright}s method were evaluated in several ways, including orange peel thickness true-estimated boxplots for the 100 orange database and various error parameters: the sum square error (SSE), the mean absolute error (MAE), the coefficient of determination (R2), the root mean square error (RMSE), and the mean square error (MSE), resulting in mean error parameter values of R2=0.854{\textpm}0.052, MSE=0.038{\textpm}0.010, and MAE=0.159{\textpm}0.023, over the test set, which to our best knowledge are remarkable numbers for an automatic and non-intrusive approach with potential application to real-time orange peel thickness estimation in the food industry. }, doi = {http://dx.doi.org/10.5424/sjar/2018164-11185}, url = {https://revistas.inia.es/index.php/sjar/article/view/11185}, author = {H Javadikia and S Sabzi and J I Arribas} } @article {859, title = {A new approach for the design of digital frequency selective FIR fillters using an FPA-based algorithm}, journal = {Expert Systems with Applications}, volume = {106}, year = {2018}, chapter = {92-106}, abstract = {Efficient digital filter design is an essential signal processing task. Finite Impulse Response (FIR) filters are used in many applications due to its properties of linear phase and frequency stability. Most traditional design methods suffer from the problem of insufficient control over the frequency response of the designed filter. For this reason, the use of a recently developed optimisation technique called flowers pollination algorithm (FPA), {\textendash}based on the natural process of pollination of flowers{\textendash} along with a novel multiple fitness function, is proposed in order to obtain optimised filter coefficients that best approximate ideal specifications. Results have been compared to both traditional methods (mainly windowing and the Parks-McClellan algorithm) as well as to several nature-inspired schemes. Finally, processing of a real EEG signal is used to quantitatively evaluate performance of designed filters. Numerical results show that our method achieves better fit to desired filter specifications, a 5-10 times larger attenuation in the stop band and a narrower transition band, at the expense of slightly increasing the pass-band ripple (5-15\%) in 3 out of 4 of the cases.}, doi = {https://doi.org/10.1016/j.eswa.2018.03.045}, url = {https://www.sciencedirect.com/science/article/pii/S095741741830191X}, author = {L M San-Jose-Revuelta and J I Arribas} } @conference {740, title = {ADC-Weighted Joint Registration-Estimation for Cardiac Diffusion Magnetic Resonance Imaging}, booktitle = {Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, year = {2017}, month = {12/2017}, abstract = {

The purpose of this work is to develop a method for the groupwise registration of diffusion weighted datasets of the heart which automatically provide smooth Apparent Diffusion Coefficient (ADC) estimations, by making use of a novel multimodal scheme. To this
end, we have introduced a joint methodology that simultaneously performs both the alignment of the images and the ADC estimation. In order to promote diffeomorphic transformations and to avoid undesirable noise amplification, we have included appropriate
smoothness constraints for both problems under the same formulation. The implemented multimodal registration metric incorporates the ADC estimation residuals, which are inversely weighted with the b-values to balance the influence of the signal level for each diffusion weighted image. Results show that the joint formulation provides more robust and precise ADC estimations and a significant improvement in the overlap of the contour
of manual delineations along the different b-values. The proposed algorithm is able to effectively deal with the presence of both physiological motion and inherent contrast variability for the different b-value images, increasing accuracy and robustness of the estimation of diffusion parameters for cardiac imaging.

}, author = {Santiago Sanz-Est{\'e}banez and J Royuela-del-Val and Jordi Broncano-Cabrero and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @article {698, title = {Abnormal Capillary Vasodynamics Contribute to Ictal Neurodegeneration in Epilepsy}, journal = {Scientific Reports}, volume = {7}, year = {2017}, abstract = {

Seizure-driven brain damage in epilepsy accumulates over time, especially in the hippocampus, which can lead to sclerosis, cognitive decline, and death. Excitotoxicity is the prevalent model to explain ictal neurodegeneration. Current labeling technologies cannot distinguish between excitotoxicity and hypoxia, however, because they share common molecular mechanisms. This leaves open the possibility that undetected ischemic hypoxia, due to ictal blood flow restriction, could contribute to neurodegeneration previously ascribed to excitotoxicity. We tested this possibility with Confocal Laser Endomicroscopy (CLE) and novel stereological analyses in several models of epileptic mice. We found a higher number and magnitude of NG2+ mural-cell mediated capillary constrictions in the hippocampus of epileptic mice than in that of normal mice, in addition to spatial coupling between capillary constrictions and oxidative stressed neurons and neurodegeneration. These results reveal a role for hypoxia driven by capillary blood flow restriction in ictal neurodegeneration. {\textcopyright} 2017 The Author(s).

}, doi = {10.1038/srep43276}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85014072909\&doi=10.1038\%2fsrep43276\&partnerID=40\&md5=e9d3567266bdc360a7addc92be350c8d}, author = {Leal-Campanario, R. and Alarcon-Martinez, L. and Rieiro, H. and Martinez-Conde, S. and Alarcon-Martinez, T. and Zhao, X. and LaMee, J. and Popp, P.J. and Calhoun, M.E. and J I Arribas and Schlegel, A.A. and Di Stasi, L.L. and Rho, J.M. and Inge, L. and Otero-Millan, J. and Treiman, D.M. and Macknik, S.L.} } @conference {700, title = {Groupwise Non-Rigid Registration on Multiparametric Abdominal DWI Acquisitions for Robust ADC Estimation: Comparison with Pairwise Approaches and Different Multimodal Metrics}, booktitle = {International Symposium on Biomedical Imaging: From Nano to Macro (ISBI2017)}, year = {2017}, month = {2017}, address = {Melbourne, Australia}, abstract = {

Registration of diffusion weighted datasets remains a challenging\ task in the process of quantifying diffusion indexes.\ Respiratory and cardiac motion, as well as echo-planar characteristic\ geometric distortions, may greatly limit accuracy on\ parameter estimation, specially for the liver. This work proposes\ a methodology for the non-rigid registration of multiparametric\ abdominal diffusion weighted imaging by using\ different well-known metrics under the groupwise paradigm.\ A three-stage validation of the methodology is carried out on\ a computational diffusion phantom, a watery solution phantom\ and a set of voluntary patients. Diffusion estimation\ accuracy has been directly calculated on the computational\ phantom and indirectly by means of a residual analysis on\ the real data. On the other hand, effectiveness in distortion\ correction has been measured on the phantom. Results have\ shown statistical significant improvements compared to pairwise\ registration being able to cope with elastic deformations.

}, author = {Santiago Sanz-Est{\'e}banez and {\'O}scar Pe{\~n}a-Nogales and Rodrigo de Luis-Garc{\'\i}a and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @article {743, title = {Libstable: Fast, parallel, and high-precision computation of α-stable distributions in R, C/C++, and MATLAB}, journal = {Journal of Statistical Software}, volume = {78}, year = {2017}, pages = {1-25}, doi = {10.18637/jss.v078.i01}, author = {J Royuela-del-Val and Federico Simmross-Wattenberg and Carlos Alberola-Lopez} } @article {666, title = {Non-Stationary Rician Noise Estimation in Parallel MRI using a Single Image: a Variance-Stabilizing Approach}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {39}, year = {2017}, month = {2017}, pages = {2015-2029}, chapter = {2015}, abstract = {

Parallel magnetic resonance imaging (pMRI) techniques have gained a great importance both in research and clinical communities recently since they considerably accelerate the image acquisition process. However, the image reconstruction algorithms needed to correct the subsampling artifacts affect the nature of noise, i.e. it becomes non-stationary. Some methods have been proposed in the literature dealing with the non-stationary noise in pMRI. However, their performance depends on information not usually available such as multiple acquisitions, receiver noise matrices, sensitivity coil profiles, reconstruction coefficients, or even biophysical models of the data. Besides, some methods show an undesirable granular pattern on the estimates as a side effect of local estimation. Finally, some methods make strong assumptions that just hold in the case of high signal-to-noise ratio (SNR), which limits their usability in real scenarios. We propose a new automatic noise estimation technique for non-stationary Rician noise that overcomes the aforementioned drawbacks. Its effectiveness is due to the derivation of a variance-stabilizing transformation designed to deal with any SNR. The method was compared to the main state-of-the-art methods in synthetic and real scenarios. Numerical results confirm the robustness of the method and its better performance for the whole range of SNRs.

}, issn = {0162-8828}, doi = {10.1109/TPAMI.2016.2625789}, author = {Tomasz Pieciak and Santiago Aja-Fern{\'a}ndez and Gonzalo Vegas S{\'a}nchez-Ferrero} } @conference {871, title = {Non-intrusive image processing Thompson orange grading methods}, booktitle = {2017 56th FITCE Congress}, year = {2017}, publisher = {IEEE}, organization = {IEEE}, abstract = {A key issue in fruit export is classification and sorting for marketing. In this work image processing techniques are used to grad Thompson orange fruit. For this purpose, fourteen parameters were extracted, comprising area, eccentricity, perimeter, length/area, blue value, green value, red value, width, contrast, texture, width/area, width/length, roughness, and length. Adaptive neuro fuzzy inference system (ANFIS), linear, and nonlinear regression methods were used. Based on results, mean square error (MSB), sum squared error (SSE) and coefficient of determination (R 2 ) were 3.47e-08, 3.47e-07, 0.988 (ANFIS), 51.33, 4927.59, 0.866 (linear reg.) and 64.85, 6092.5, 0.832 (non-linear reg.), respectively. ANFIS model was shown as the best fit model based on previously listed performance evaluation criteria.}, doi = {https://doi.org/10.1109/FITCE.2017.8093004}, url = {https://ieeexplore.ieee.org/abstract/document/8093004}, author = {Sabzi, Sajad and Yousef Abbaspour-Gilandeh and J I Arribas} } @article {873, title = {A blood orange computer vision sorting system}, year = {2017}, abstract = {To have a proper sorting system with a low error rate can be very useful in automatic packaging of products. Furthermore, physical dimensions and shape are important in sorting and sizing of fruits and vegetables. In this paper Iranian orange (blood orange) are considered to present an automatic mass sorting system with low error rate using image processing coupled with an adaptive neurofuzzy inference system (ANFIS). Linear regression analysis was used to compare results and an efficient algorithm was designed and implemented in MatLab. This algorithm is able to measure area, eccentricity, perimeter, length/area, red, green, and blue RGB components, width, contrast, texture, width/area, width/length, roughness and length. In ANFIS model, samples were divided into two sets: 70\% for training and 30\% for testing. Best ANFIS, linear and nonlinear regression models, yielded values of the coefficient of determination (R2), sum squared error (SSE), and mean squared error (MSE) of 0.989, 21.46, 1.65 (ANFIS), 0.91, 1156.69, 12.05 (linear) and 0.88, 1538.10, 15.86 (nonlinear), respectively. Based on results, ANFIS model showed clearly better capability for mass prediction compared to both linear and nonlinear regression. A prototype for an automatic non-intrusive orange mass sorting system is depicted to conclude.}, doi = {https://doi.org/10.1049/cp.2017.0167}, url = {https://digital-library.theiet.org/content/conferences/10.1049/cp.2017.0167}, author = {Sabzi, Sajad and Yousef Abbaspour-Gilandeh and J I Arribas} } @conference {872, title = {A new method based on computer vision for non-intrusive orange peel sorting}, booktitle = {2017 56th FITCE Congress}, year = {2017}, publisher = {IEEE}, organization = {IEEE}, abstract = {As it is well-known, orange peel is used for making jam and oil. For this purpose, orange samples with high peel thickness are best. In order to predict peel thickness in orange fruit, we present a system based in image features, comprising: area, eccentricity, perimeter, length/area, blue value, green value, red value, wide, contrast, texture, wide/area, wide/length, roughness, and length. A novel identification solution based on the hybrid of particle swarm optimization (PSO), genetic algorithm (GA) and artificial neural network (ANN) is proposed. In addition, principal component analysis (PCA) has been applied to reduce the number of dimensions, without much loss of information. Taguchi{\textquoteright}s robust optimization technique has been applied to determine the optimal setting for parameters of PSO, GA, and ANN. The optimal level of factors were: Number of Neuron in first layer=7, Number of Neuron in second layer=2, Maximum Iteration=400, Crossover probability=0.7, Mutation probability=0.1, and Swarm (Population) Size=200. Results for prediction of orange peel thickness based on levels that are achieved by Taguchi method were evaluated by five performance measures: the coefficient of determination (R 2 ), mean squared error (MSE), mean absolute error (MAE), sum square error (SSE), and root mean square error (RMSE), reaching values of 0.8571, 0.0123, 0.0924, 1.392, and 0.1109, respectively.}, doi = {https://doi.org/10.1109/FITCE.2017.8093001}, url = {https://ieeexplore.ieee.org/abstract/document/8093001}, author = {Sabzi, Sajad and Yousef Abbaspour-Gilandeh and J I Arribas} } @conference {600, title = {An Automated Tensorial Classification Procedure for Left Ventricular Hypertrophic Cardiomyopathy}, booktitle = {IWBBIO 2016 (4th International Work-Conference on Bioinformatics and Biomedical Engineering)}, volume = {1}, year = {2016}, month = {2016}, pages = {1-12}, edition = {LNBI 9656}, address = {Granada, Spain}, abstract = {

Cardiovascular diseases are the leading cause of death globally. Therefore, classi cation tools play a major role in prevention and\ treatment of these diseases. Statistical learning theory applied to magnetic resonance imaging has led to the diagnosis of a variety of cardiomyopathies states.\ We propose a two-stage classi cation scheme capable of\ distinguishing between heterogeneous groups of hypertrophic cardiomyopathies and healthy patients.\ A multimodal processing pipeline is employed to estimate robust tensorial descriptors of myocardial mechanical\ properties for both short-axis and long-axis magnetic resonance tagged\ images using the least absolute deviation method. A homomorphic ltering procedure is used to align the cine segmentations to the tagged sequence and provides 3D tensor information in meaningful areas.\ Results\ have shown that the proposed pipeline provides tensorial measurements\ on which classi ers for the study of hypertrophic cardiomyopathies can\ be built with acceptable performance even for reduced samples sets.

}, keywords = {Fuzzy clustering, HARmonic Phase, Homomorphic Filtering, Hypertrophic Cardiomyopathy, Least Absolute Deviation, Magnetic Resonance Tagging, Support Vector Machines}, doi = {10.1007/978-3-319-31744-1 17}, author = {Santiago Sanz-Est{\'e}banez and J Royuela-del-Val and S. Merino-Caviedes and A. Revilla-Orodea and T. Sevilla-Ruiz and Martin-Fernandez, M and Carlos Alberola-Lopez} } @conference {663, title = {Cardio-respiratory motion estimation for compressed sensing reconstruction of free-breathing 2D cine MRI}, booktitle = {Modulated/Incomplete Data 2016, SFB Workshop.}, year = {2016}, month = {2016}, publisher = {Mathematical Optimization and Applications in Biomedical Sciences (MOBIS), SFB Research Center}, organization = {Mathematical Optimization and Applications in Biomedical Sciences (MOBIS), SFB Research Center}, address = {Graz, Austria}, abstract = {

Respiratory motion is still an issue in MRI of the heart despite the introduction of Compressed Sensing (CS) techniques, which significantly accelerate acquisition [1]. Recently [2], a double-binning scheme was introduced in which k-space data is split according both to the cardiac and respiratory phases (Fig. 1); at reconstruction, sparsity along both dimensions is exploited. Other methods introduce motion estimation and compensation in CS (MC-CS) either to correct the respiratory motion [3] or to promote sparsity for reconstruction improvement [4]. In this work, we propose a technique to jointly estimate the respiratory and cardiac motions within a double-binning scheme, enabling the MC-CS reconstruction of respiratory resolved free-breathing 2D CINE MRI. Preliminary results on synthetic, highly undersampled (x16) Cartesian setup are shown.

[1] Lustig et al. MRM 2007, [2] Feng et al. MRM 2015, [3] Usman et al. MRM 2013. [4]\ Royuela-del-Val et al. MRM 2015.

}, author = {J Royuela-del-Val and Marcos Mart{\'\i}n-Fern{\'a}ndez and Federico Simmross-Wattenberg and Carlos Alberola-Lopez} } @conference {687, title = {Harmonic Auto-Regularization for Non Rigid Groupwise Registration in Cardiac Magnetic Resonance Imaging.}, booktitle = {Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica 2016}, year = {2016}, month = {11/2016}, address = {Valencia, Spain}, abstract = {

In this paper we present a new approach for non rigid groupwise registration of cardiac magnetic resonance images by means of free-form deformations, imposing a prior harmonic deformation assumption. The procedure proposes a primal-dual framework for solving an equality constrained minimization problem, which allows an automatic estimate of the trade-off between image fidelity and the Laplacian smoothness terms for each iteration. The method has been applied to both a 4D extended cardio-torso phantom and to a set of voluntary patients. The accuracy of the method has been measured for the synthetic experiment as the difference in modulus between the estimated displacement field and the ground truth; as for the real data, we have calculated the Dice coefficient between the contour manual delineations provided by two cardiologists at end systolic phase and those provided by them at end diastolic phase and, consequently propagated by the registration algorithm to the systolic instant. The automatic procedure turns out to be competitive in motion compensation with other methods even though their parameters have been previously set for optimal performance in different scenarios.

}, author = {Santiago Sanz-Est{\'e}banez and J Royuela-del-Val and T. Sevilla-Ruiz and Revilla-Orodea, A. and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @article {602, title = {Jacobian weighted temporal total variation for motion compensated compressed sensing reconstruction of dynamic MRI}, journal = {Magnetic Resonance in Medicine}, year = {2016}, month = {2016}, abstract = {

Purpose:\ To eliminate the need of spatial intraframe regularization in a recently reported dynamic MRI compressed-sensing-based reconstruction method with motion compensation and to increase its performance.

Theory and Methods: We propose a new regularization metric based on the introduction of a spatial weighting measure given by the Jacobian of the estimated deformations. It shows convenient discretization properties and, as a byproduct, it also provides a theoretical support to a result reported by others based on an intuitive design. The method has been applied to the reconstruction of both short and long axis views of the heart of four healthy volunteers. Quantitative image quality metrics as well as straightforward visual assessment are reported.

Results: Short and long axis reconstructions of cardiac cine MRI sequences have shown superior results than previously reported methods both in terms of quantitative metrics and of visual assessment. Fine details are better preserved due to the lack of additional intraframe regularization, with no significant image artifacts even for an acceleration factor of 12.

Conclusions: The proposed Jacobian Weighted temporal Total Variation results in better reconstructions of highly undersampled cardiac cine MRI than previously proposed methods and sets a theoretical ground for forward and backward predictors used elsewhere.

}, keywords = {compressed sensing, dynamic MRI reconstruction, group-wise registration, motion estimation}, doi = {10.1002/mrm.26198}, url = {http://onlinelibrary.wiley.com/doi/10.1002/mrm.26198}, author = {J Royuela-del-Val and Lucilio Cordero-Grande and Federico Simmross-Wattenberg and Mart{\'\i}n-Fern{\'a}ndez, M and Carlos Alberola-Lopez} } @article {597, title = {Multi-oriented windowed harmonic phase reconstruction for robust cardiac strain imaging}, journal = {Medical Image Analysis}, volume = {29}, year = {2016}, month = {2016}, pages = {1-11}, chapter = {1}, author = {Lucilio Cordero-Grande and J Royuela-del-Val and Santiago Sanz-Est{\'e}banez and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {603, title = {Multiresolution Reconstruction of Real-Time MRI with Motion Compensated Compressed Sensing: Application to 2D Free-Breathing Cardiac MRI}, booktitle = {International Symposium on Biomedical Engineering: From Nano to Macro}, year = {2016}, month = {2016}, publisher = {IEEE Signal Processing Society}, organization = {IEEE Signal Processing Society}, address = {Prague, Check Republic}, abstract = {

Real-time MRI is a novel noninvasive imaging technique that allows the visualization of physiological processes with both good spatial and temporal resolutions. However, the reconstruction of images from highly undersampled data, needed to perform real-time imaging, remains challenging. Recently, the combination of Compressed Sensing theory with motion compensation techniques has shown to achieve better results than previous methods. In this work we describe a real-time MRI algorithm based on the acquisition of the k-space data following a Golden Radial trajectory, Compressed Sensing reconstruction and a groupwise temporal registration algorithm for the estimation and compensation of the motion in the image, all this embedded within a temporal multiresolution scheme. We have applied the proposed method to the reconstruction of free-breathing acquisition of short axis views of the heart, achieving a temporal resolution of 25ms, corresponding to an acceleration factor of 28 with respect to fully sampled Cartesian acquisitions.

}, keywords = {Compressive sensing \& sampling, Image reconstruction {\textendash} analytical \& iterative methods, Magnetic resonance imaging (MRI)}, author = {J Royuela-del-Val and Muhammad Usman and Lucilio Cordero-Grande and M. Mart{\'\i}n-Fern{\'a}ndez and Federico Simmross-Wattenberg and Claudia Prieto and Carlos Alberola-Lopez} } @conference {615, title = {Spatial and Spectral Anisotropy in HARP Images: An Automated Approach}, booktitle = {International Symposium on Biomedical Imaging: From Nano to Macro (ISBI2016)}, year = {2016}, month = {2016}, address = {Prague, Czech Republic}, abstract = {

Strain and related tensors play a major role in cardiac function\ characterization, so correct estimation of the local phase\ in tagged images is crucial for quantitative myocardial motion\ studies. We propose an Harmonic Phase related procedure\ that is adaptive in the spatial and the spectral domains: as for\ the former, we use an angled-steered analysis window prior to\ the Fourier Transform; as for the latter, the bandpass filter is\ also angle-adaptive. Both of them are narrow in the modulation\ direction and wide in the orthogonal direction.

Moreover,\ no parameters are manually set since their values are partially\ based on the information available at the DICOM headers and\ additional information is estimated from data. The procedure
is tested in terms of accuracy (on synthetic data) and reproducibility\ (on real data) of the deformation gradient tensor,\ measured by means of the distribution of the Frobenius norm\ differences between two tensor datasets.

}, keywords = {Anisotropic Gaussian Window, Automatic Band-Pass Filtering, HARmonic Phase, Strain Tensor, Tagged Magnetic Resonance Imaging, Thresholding}, author = {Santiago Sanz-Est{\'e}banez and Lucilio Cordero-Grande and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {SanJos{\'e}Revuelta2016561, title = {Three Natural Computation methods for joint channel estimation and symbol detection in multiuser communications}, journal = {Applied Soft Computing}, volume = {49}, year = {2016}, pages = {561 - 569}, abstract = {Abstract This paper studies three of the most important optimization algorithms belonging to Natural Computation (NC): genetic algorithm (GA), tabu search (TS) and simulated quenching (SQ). A concise overview of these methods, including their fundamentals, drawbacks and comparison, is described in the first half of the paper. Our work is particularized and focused on a specific application: joint channel estimation and symbol detection in a Direct-Sequence/Code-Division Multiple-Access (DS/CDMA) multiuser communications scenario; therefore, its channel model is described and the three methods are explained and particularized for solving this. Important issues such as suboptimal convergence, cycling search or control of the population diversity have deserved special attention. Several numerical simulations analyze the performance of these three methods, showing, as well, comparative results with well-known classical algorithms such as the Minimum Mean Square Error estimator (MMSE), the Matched Filter (MF) or Radial Basis Function (RBF)-based detection schemes. As a consequence, the three proposed methods would allow transmission at higher data rates over channels under more severe fading and interference conditions. Simulations show that our proposals require less computational load in most cases. For instance, the proposed \{GA\} saves about 73\% of time with respect to the standard GA. Besides, when the number of active users doubles from 10 to 20, the complexity of the proposed \{GA\} increases by a factor of 8.33, in contrast to 32 for the optimum maximum likelihood detector. The load of \{TS\} and \{SQ\} is around 15{\textendash}25\% higher than that of the proposed GA.}, keywords = {Population diversity}, issn = {1568-4946}, doi = {http://dx.doi.org/10.1016/j.asoc.2016.08.034}, url = {http://www.sciencedirect.com/science/article/pii/S1568494616304288}, author = {Luis M. San-Jos{\'e}-Revuelta and J I Arribas} } @conference {690, title = {Whole-heart single breath-hold cardiac cine: A robust motion-compensated compressed sensing reconstruction method}, booktitle = {International Workshop on Reconstruction and Analysis of Moving Body Organs (RAMBO/MICCAI) }, year = {2016}, month = {2016}, address = {Athens, Greece}, author = {J Royuela-del-Val and Muhammad Usman and Lucilio Cordero-Grande and Marcos Mart{\'\i}n-Fern{\'a}ndez and Federico Simmross-Wattenberg and Claudia Prieto and Carlos Alberola-Lopez} } @article {7460246, title = {A computer-aided diagnosis system with EEG based on the P3b wave during an auditory odd-ball task in schizophrenia}, journal = {IEEE Transactions on Biomedical Engineering}, volume = {PP}, number = {99}, year = {2016}, pages = {1-1}, abstract = {Objective: To design a Computer-aided diagnosis (CAD) system using an optimized methodology over the P3b wave in order to objectively and accurately discriminate between healthy controls (HC) and schizophrenic subjects (SZ). Methods: We train, test, analyze, and compare various machine learning classification approaches optimized in terms of the correct classification rate (CCR), the degenerated Youden{\textquoteright}s index (DYI) and the area under the receiver operating curve (AUC). CAD system comprises five stages: electroencephalography (EEG) preprocessing, feature extraction, seven electrode groupings, discriminant feature selection, and binary classification. Results: With two optimal combinations of electrode grouping, filtering, feature selection algorithm, and classification machine, we get either a mean CCR = 93.42\%, specificity = 0.9673, sensitivity = 0.8727, DYI = 0.9188, and AUC = 0.9567 (total-15 Hz-J5-MLP), or a mean CCR = 92.23\%, specificity = 0.9499, sensitivity = 0.8838, DYI = 0.9162, and AUC = 0.9807 (right hemisphere-35 Hz-J5-SVM), which to our knowledge are higher than those available to date. Conclusions: We have verified that a more restrictive low-pass filtering achieves higher CCR as compared to others at higher frequencies in the P3b wave. In addition, results validate previous hypothesis about the importance of the parietal-temporal region, associated with memory processing, allowing us to identify powerful {feature,electrode} pairs in the diagnosis of schizophrenia, achieving higher CCR and AUC in classification of both right and left Hemispheres, and parietal-temporal EEG signals, like, for instance, the {PSE, P4} pair (J5 and mutual information feature selection). Significance: Diagnosis of schizophrenia is made thoroughly by psychiatrists but as any human-based decision that has a subjective component. This CAD system provides the human expert with an objective complimentary measure to help him in diagnosing schizophrenia.}, keywords = {Computer aided diagnosis, Design automation, Electrodes, Electroencephalography, Feature extraction, Indexes, Sensitivity}, issn = {0018-9294}, doi = {10.1109/TBME.2016.2558824}, url = {https://ieeexplore.ieee.org/abstract/document/7460246}, author = {L. Santos-Mayo and Luis Miguel San-Jose-Revuelta and J I Arribas} } @conference {598, title = {Cardiac Strain Assessment for Fibrotic Myocardial Tissue Detection in Left Ventricular Hypertrophic Cardiomyopathy}, booktitle = {XXXIII Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica.}, year = {2015}, month = {2015}, address = {Madrid, Spain.}, abstract = {

This work proposes an image processing methodology to\ distinguish fibrotic from normal tissue by the assessment of the\ local mechanical properties of the myocardium in magnetic\ resonance tagging images. The procedure uses the information\ provided by short axis images of the above mentioned modality\ to estimate the Green-Lagrange strain tensor; a modified\ method based on the Harmonic Phase is employed for motion\ estimation. The method has been applied to the analysis of the\ local deformation patterns in a set of patients affected by\ hypertrophic cardiomyopathy in order to find the agreement\ between hyperenhanced zones in late enhancement images and\ areas in the myocardium with abnormal tensor values (both the\ radial and the circumferential components as well as the\ shearing component have been accounted for). The agreement is\ measured taken as ground truth manual segmentation of late\ enhancement images carried out by two cardiologists. Finally, a\ set of example images illustrate the agreement between both\ techniques.

}, author = {Santiago Sanz-Est{\'e}banez and S. Merino-Caviedes and T. Sevilla-Ruiz and A. Revilla-Orodea and Mart{\'\i}n-Fern{\'a}ndez, M and Carlos Alberola-Lopez} } @article {628, title = {Efficient and Robust Image Restoration Using Multiple-Feature L2-Relaxed Sparse Analysis Priors}, journal = {IEEE Transactions on Image Processing}, volume = {24}, year = {2015}, month = {Dec}, pages = {5046-5059}, abstract = {

We propose a novel formulation for relaxed analysis-based sparsity in multiple dictionaries as a general type of prior for images, and apply it for Bayesian estimation in image restoration problems. Our formulation of a l2 -relaxed l0 pseudo-norm prior allows for an especially simple maximum a posteriori estimation iterative marginal optimization algorithm, whose convergence we prove. We achieve a significant speedup over the direct (static) solution by using dynamically evolving parameters through the estimation loop. As an added heuristic twist, we fix in advance the number of iterations, and then empirically optimize the involved parameters according to two performance benchmarks. The resulting constrained dynamic method is not just fast and effective, it is also highly robust and flexible. First, it is able to provide an outstanding tradeoff between computational load and performance, in visual and objective, mean square error and structural similarity terms, for a large variety of degradation tests, using the same set of parameter values for all tests. Second, the performance benchmark can be easily adapted to specific types of degradation, image classes, and even performance criteria. Third, it allows for using simultaneously several dictionaries with complementary features. This unique combination makes ours a highly practical deconvolution method.

}, keywords = {Bayes methods, Bayesian estimation, Convergence, Dictionaries, Estimation, Kernel, L2-relaxed L0 pseudo norm, L2-relaxed L0 pseudo-norm prior, L2-relaxed sparse analysis priors, Maximum likelihood estimation, Optimization, Redundancy, computational load, constrained dynamic method, deconvolution, deconvolution method, dynamically evolving parameters, estimation loop, fast constrained dynamic algorithm, image restoration, iterative marginal optimization, iterative methods, maximum a posteriori estimation, mean square error, mean square error methods, multiple representations, multiple-feature L2-relaxed sparse analysis priors, optimisation, robust tunable parameters, structural similarity terms}, issn = {1057-7149}, doi = {10.1109/TIP.2015.2478405}, author = {Javier Portilla and Antonio Trist{\'a}n-Vega and Ivan W. Selesnick} } @article {431, title = {Fast calculation of alpha-stable density functions based on off-line precomputations. Application to ML parameter estimation}, journal = {Digital Signal Processing}, volume = {38}, year = {2015}, pages = {1-12}, chapter = {1}, keywords = {Delaunay triangulation, Interpolation, Parameter estimation, alpha-Stable}, doi = {10.1016/j.dsp.2014.12.009}, author = {Federico Simmross-Wattenberg and Marcos Mart{\'\i}n-Fern{\'a}ndez and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez} } @conference {588, title = {Multiresolution Reconstruction of Real-Time MRI with Motion Compensated Compressed Sensing: Application to 2D Free-Breathing Cardiac MRI}, booktitle = {XXXIII Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica (CASEIB)}, year = {2015}, month = {11/2015}, address = {Madrid}, author = {J Royuela-del-Val and Muhammad Usman and Lucilio Cordero-Grande and Marcos Martin-Fernandez and Federico Simmross-Wattenberg and Claudia Prieto and Carlos Alberola-Lopez} } @article {533, title = {Non-Rigid Groupwise Registration for Motion Estimation and Compensation in Compressed Sensing Reconstruction of Breath-Hold Cardiac Cine MRI}, journal = {Magnetic Resonance in Medicine}, year = {2015}, doi = {10.1002/mrm.25733}, author = {J Royuela-del-Val and Lucilio Cordero-Grande and Federico Simmross-Wattenberg and Marcos Mart{\'\i}n-Fern{\'a}ndez and Carlos Alberola-Lopez} } @inbook {572, title = {PPG Beat Reconstruction Based on Shape Models and Probabilistic Templates for Signals Acquired with Conventional Smartphones}, booktitle = {Lecture Notes in Computer Science}, volume = {9117}, year = {2015}, pages = {595{\textendash}602}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Domingues, Alexandre and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez and Sanches, J Miguel} } @conference {520, title = {Single Breath Hold Whole Heart Cine MRI With Iterative Groupwise Cardiac Motion Compensation and Sparse Regularization (kt-WiSE)}, booktitle = {Proceedings of the International Society for Magnetic Resonance in Medicine 23}, year = {2015}, author = {J Royuela-del-Val and Muhammad Usman and Lucilio Cordero-Grande and Federico Simmross-Wattenberg and Marcos Martin-Fern{\'a}ndez and Claudia Prieto and Carlos Alberola-Lopez} } @article {568, title = {Spherical Deconvolution of Multichannel Diffusion MRI Data with Non-Gaussian Noise Models and Spatial Regularization}, journal = {PLoS ONE}, volume = {10}, year = {2015}, pages = {e0138910}, doi = {10.1371/journal.pone.0138910}, url = {http://dx.doi.org/10.1371\%2Fjournal.pone.0138910}, author = {Canales-Rodr{\'\i}guez, Erick J. and Daducci, Alessandro and Stamatios N. Sotiropoulos and Caruyer, Emmanuel and Santiago Aja-Fern{\'a}ndez and Radua, Joaquim and Yurramendi Mendizabal, Jes{\'u}s M. and Iturria-Medina, Yasser and Melie-Garc{\'\i}a, Lester and Alem{\'a}n-G{\'o}mez, Yasser and J-P Thiran and Sarr{\'o}, Salvador and Pomarol-Clotet, Edith and Salvador, Raymond} } @conference {656, title = {Tissue and Label Modelling for Segmentation of Scar with Contour Correction in Cardiac DE-CMR Volumes}, booktitle = {XXXIII Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, year = {2015}, month = {2015}, address = {Madrid, Spain}, author = {S. Merino-Caviedes and Lucilio Cordero-Grande and P{\'e}rez Rodr{\'\i}guez, M Teresa and T. Sevilla-Ruiz and A. Revilla-Orodea and Mart{\'\i}n-Fern{\'a}ndez, Marcos and Carlos Alberola-Lopez} } @conference {589, title = {Tissue and Label Modelling for Segmentation of Scar with Contour Correction in Cardiac DE-CMR Volumes}, booktitle = {XXXIII Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, year = {2015}, month = {11/2015}, address = {Madrid, Spain}, abstract = {Most scar segmentation methods for cardiac DE-CMR images are constrained by a previous myocardial segmentation that provides borders for the scar identification. However, the automation of these methods rely on an existing myocardial segmentation from CINE-CMR that is registered to the DE-CMR volume; in this step, however, alignment errors are usually introduced and they carry over to the labeling operation. These errors typically remain unchanged after tissue labeling, so inconsistencies between the two (alignment and labeling) may exist. We explore this issue and present a method that, with the same inputs, identifies the healthy and scarred tissue and selectively corrects the endocardial and epicardial contours depending on the image edges, the estimated probabilistic distributions and the proximity to the aligned myocardial borders. For this, we model the posterior probability of each ROI label with a Bayesian approach that unifies the prior tissue probabilities and the myocardial labels. The maximum a posteriori criterion is used to compute a first DE-CMR label map, which is afterwards refined by a connected component analysis. Preliminary results show better accuracy for the endocardial and epicardial contours, and the segmented scar compares favorably with respect to state of the art methods.}, author = {S. Merino-Caviedes and Lucilio Cordero-Grande and P{\'e}rez Rodr{\'\i}guez, M. T. and T. Sevilla-Ruiz and A. Revilla-Orodea and Mart{\'\i}n-Fern{\'a}ndez, M. and Carlos Alberola-Lopez} } @inbook {vegas2014gamma, title = {A Gamma Mixture Model for IVUS Imaging}, booktitle = {Multi-Modality Atherosclerosis Imaging and Diagnosis}, year = {2014}, pages = {155{\textendash}171}, publisher = {Springer New York}, organization = {Springer New York}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Marcos Martin-Fernandez and Sanches, J Miguel} } @article {vegas2014gamma, title = {Gamma mixture classifier for plaque detection in intravascular ultrasonic images}, journal = {Ultrasonics, Ferroelectrics and Frequency Control, IEEE Transactions on}, volume = {61}, number = {1}, year = {2014}, pages = {44{\textendash}61}, publisher = {IEEE}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Seabra, Jose and Rodriguez-Leor, Oriol and Serrano-Vida, Angel and Santiago Aja-Fern{\'a}ndez and Palencia, C and Marcos Martin-Fernandez and Sanches, J} } @conference {571, title = {HLS based hardware acceleration on the zynq SoC: A case study for fall detection system}, booktitle = {IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA 2014)}, year = {2014}, address = {Doha, Qatar}, author = {Ait Si Ali, Amine and Siupik, Marek and Amira, Abbes and Bensaali, Faycal and Pablo Casaseca-de-la-Higuera} } @article {476, title = {Localized abnormalities in the cingulum bundle in patients with schizophrenia: A Diffusion Tensor tractography study}, journal = {NeuroImage: Clinical}, volume = {5}, year = {2014}, pages = {93{\textendash}99}, abstract = {

The cingulum bundle (CB) connects gray matter structures of the limbic system and as such has been implicated in the etiology of schizophrenia. There is growing evidence to suggest that the CB is actually comprised of a conglomeration of discrete sub-connections. The present study aimed to use Diffusion Tensor tractography to subdivide the CB into its constituent sub-connections, and to investigate the structural integrity of these sub-connections in patients with schizophrenia and matched healthy controls. Diffusion Tensor Imaging scans were acquired from 24 patients diagnosed with chronic schizophrenia and 26 matched healthy controls. Deterministic tractography was used in conjunction with FreeSurfer-based regions-of-interest to subdivide the CB into 5 sub-connections (I1 to I5). The patients with schizophrenia exhibited subnormal levels of FA in two cingulum sub-connections, specifically the fibers connecting the rostral and caudal anterior cingulate gyrus (I1) and the fibers connecting the isthmus of the cingulate with the parahippocampal cortex (I4). Furthermore, while FA in the I1 sub-connection was correlated with the severity of patients{\textquoteright} positive symptoms (specifically hallucinations and delusions), FA in the I4 sub-connection was correlated with the severity of patients{\textquoteright} negative symptoms (specifically affective flattening and anhedonia/asociality). These results support the notion that the CB is a conglomeration of structurally interconnected yet functionally distinct sub-connections, of which only a subset are abnormal in patients with schizophrenia. Furthermore, while acknowledging the fact that the present study only investigated the CB, these results suggest that the positive and negative symptoms of schizophrenia may have distinct neurobiological underpinnings.

}, author = {Whitford, Thomas J and Lee, Sun Woo and Oh, Jungsu S and Rodrigo de Luis-Garc{\'\i}a and Savadjiev, Peter and Alvarado, Jorge L and Carl-Fredik Westin and Niznikiewicz, Margaret and Nestor, Paul G and McCarley, Robert W} } @article {canales2014spherical, title = {Spherical deconvolution of multichannel diffusion MRI data with non-Gaussian noise models and total variation spatial regularization}, journal = {arXiv preprint arXiv:1410.6353}, year = {2014}, author = {Canales-Rodr{\'\i}guez, Erick J and Daducci, Alessandro and Stamatios N. Sotiropoulos and Caruyer, Emmanuel and Santiago Aja-Fern{\'a}ndez and Radua, Joaquim and Mendizabal, Yosu Yurramendi and Iturria-Medina, Yasser and Melie-Garc{\'\i}a, Lester and Alem{\'a}n-G{\'o}mez, Yasser} } @article {de2014white, title = {White matter abnormalities in chronic migraine patients are located in anterior corpus callosum: study using a new automatic tractography selection method}, journal = {EUROPEAN JOURNAL OF NEUROLOGY}, volume = {21}, year = {2014}, pages = {51{\textendash}51}, publisher = {WILEY-BLACKWELL 111 RIVER ST, HOBOKEN 07030-5774, NJ USA}, author = {De la Cruz, C and {\'A}ngel L. Guerrero and Penas, ML and Daniel Argibay-Qui{\~n}ones and Jose M Sierra and Santiago Aja-Fern{\'a}ndez and Rodrigo de Luis-Garc{\'\i}a} } @conference {444, title = {Assessment of the fibrotic myocardial tissue mechanics by image processing}, booktitle = {Computing in Cardiology Conference (CinC), 2013}, year = {2013}, publisher = {IEEE}, organization = {IEEE}, author = {Lucilio Cordero-Grande and T. Sevilla-Ruiz and Revilla, Ana and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {443, title = {Classification of delayed enhancement scar islands by means of their local subendocardial transmurality}, booktitle = {Computing in Cardiology Conference (CinC), 2013}, year = {2013}, publisher = {IEEE}, organization = {IEEE}, author = {S. Merino-Caviedes and Lucilio Cordero-Grande and T. Sevilla-Ruiz and P{\'e}rez, Teresa and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {436, title = {Comparativa entre distribuciones alpha-estables para modelar tasas de transferencia obtenidas a partir de registros de SNMP y NetFlow}, booktitle = {Jornadas de Ingenier{\'\i}a Telem{\'a}tica (JITEL)}, year = {2013}, publisher = {Asociaci{\'o}n de Telem{\'a}tica (ATEL)}, organization = {Asociaci{\'o}n de Telem{\'a}tica (ATEL)}, address = {Granada, Spain}, author = {Stoppa, Matteo and L{\'o}pez-de-Vergara-M{\'e}ndez, Jorge E. and Federico Simmross-Wattenberg and Garc{\'\i}a-Dorado, Jos{\'e} Luis} } @conference {435, title = {Caracterizaci{\'o}n de speckle con modelos de cola pesada}, booktitle = {Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica (CASEIB)}, year = {2012}, publisher = {Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, organization = {Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, address = {San Sebasti{\'a}n, Espa{\~n}a}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Federico Simmross-Wattenberg and Marcos Martin-Fernandez and Palencia-de-Lara, C{\'e}sar and Carlos Alberola-Lopez} } @conference {434, title = {Dise{\~n}o e implementaci{\'o}n de plugins en el entorno GIMIAS para procesado y visualizaci{\'o}n de se{\~n}ales electrofisiol{\'o}gicas asociadas a problemas cardiovasculares}, booktitle = {Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica (CASEIB)}, year = {2012}, publisher = {Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, organization = {Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, address = {San Sebasti{\'a}n, Espa{\~n}a}, author = {Mart{\'\i}n-Hern{\'a}ndez, Noelia and J Royuela-del-Val and Ver{\'o}nica Garc{\'\i}a-P{\'e}rez and Federico Simmross-Wattenberg and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {casaseca2012optimal, title = {Optimal real-time estimation in diffusion tensor imaging}, journal = {Magnetic resonance imaging}, volume = {30}, number = {4}, year = {2012}, pages = {506{\textendash}517}, publisher = {Elsevier}, author = {Pablo Casaseca-de-la-Higuera and Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez and Carl-Fredik Westin and Raul San Jose-Estepar} } @inbook {cardenes2012quantitative, title = {Quantitative Analysis of Pyramidal Tracts in Brain Tumor Patients Using Diffusion Tensor Imaging}, booktitle = {Tumors of the Central Nervous System, Volume 4}, year = {2012}, pages = {143{\textendash}152}, publisher = {Springer Netherlands}, organization = {Springer Netherlands}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Emma Mu{\~n}oz-Moreno and Sarabia-Herrero, Rosario and Daniel Argibay-Qui{\~n}ones and Marcos Martin-Fernandez} } @inbook {432, title = {Ubiquitous tele-monitoring kit (UTK): measuring physiological signals anywhere at anytime}, booktitle = {Ambient Assisted Living and Home Care}, year = {2012}, pages = {183{\textendash}191}, publisher = {Springer}, organization = {Springer}, author = {Marcos-Lagunar, Carlos and Cavero-Barca, Carlos and Quintero-Padr{\'o}n, Ana Mar{\'\i}a and Planes, Xavier and Federico Simmross-Wattenberg and Carlos Alberola-Lopez and Marcos Martin-Fernandez and Mart{\'\i}n-Hern{\'a}ndez, Noelia and Calder{\'o}n-Oliveras, Enric and Corral-Herranz, Javier and Gonz{\'a}lez-Mart{\'\i}nez, A. and Huguet, Jordi and Aguilar, Rosal{\'\i}a} } @article {193, title = {Anomaly detection in network traffic based on statistical inference and alpha-stable modeling}, journal = {Dependable and Secure Computing, IEEE Transactions on}, volume = {8}, year = {2011}, pages = {494{\textendash}509}, author = {Federico Simmross-Wattenberg and Juan Ignacio Asensio-P{\'e}rez and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez and Yannis A Dimitriadis and Carlos Alberola-Lopez} } @conference {405, title = {Cuantificaci{\'o}n de la insuficiencia mitral funcional mediante el esfuerzo y la velocidad del miocardio}, booktitle = {XXIX Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, year = {2011}, address = {Centro de Cirug{\'\i}a de M{\'\i}nima Invasi{\'o}n Jes{\'u}s Us{\'o}n}, author = {Ariel H. Curiale and S{\'a}nchez-Ferrero, G Vegas and Teresa P{\'e}rez-Sanz and Santiago Aja-Fern{\'a}ndez} } @conference {arenillas2011diffusion, title = {Diffusion Tensor Imaging (DTI) Monitoring Of Motor Function Recovery After Middle Cerebral Artery Infarction: Searching For A DTI-Marker Of Neurorepair}, booktitle = {STROKE}, volume = {42}, number = {3}, year = {2011}, pages = {E119{\textendash}E119}, publisher = {LIPPINCOTT WILLIAMS \& WILKINS 530 WALNUT ST, PHILADELPHIA, PA 19106-3621 USA}, organization = {LIPPINCOTT WILLIAMS \& WILKINS 530 WALNUT ST, PHILADELPHIA, PA 19106-3621 USA}, author = {Juan F Arenillas and Daniel Argibay-Qui{\~n}ones and Garcia-Bermejo, Pablo and Calleja, Ana I and Diego Mart{\'\i}n-Mart{\'\i}nez and Jose M Sierra and Juan Jos{\'e} Fuertes-Alija and Marcos Martin-Fernandez} } @article {424, title = {Leaf classification in sunflower crops by computer vision and neural networks}, journal = {Computers and Electronics in Agriculture}, volume = {78}, year = {2011}, pages = {9-18}, abstract = {

In this article, we present an automatic leaves image classification system for sunflower crops using neural networks, which could be used in selective herbicide applications. The system is comprised of four main stages. First, a segmentation based on rgb color space is performed. Second, many different features are detected and then extracted from the segmented image. Third, the most discriminable set of features are selected. Finally, the Generalized Softmax Perceptron (GSP) neural network architecture is used in conjunction with the recently proposed Posterior Probability Model Selection (PPMS) algorithm for complexity selection in order to select the leaves in an image and then classify them either as sunflower or non-sunflower. The experimental results show that the proposed system achieves a high level of accuracy with only five selected discriminative features obtaining an average Correct Classification Rate of 85\% and an area under the receiver operation curve over 90\%, for the test set. {\^A}{\textcopyright} 2011 Elsevier B.V.

}, keywords = {Classification rates, Computer vision, Crops, Discriminative features, Generalized softmax perceptron, Helianthus, Herbicide application, Herbicides, Image classification, Image classification systems, Leaf classification, Learning machines, Model selection, Network architecture, Neural networks, Posterior probability, RGB color space, Segmented images, Sunflower, Test sets, accuracy assessment, agricultural technology, algorithm, artificial neural network, automation, dicotyledon, experimental study, herbicide, segmentation}, issn = {01681699}, doi = {10.1016/j.compag.2011.05.007}, url = {https://www.sciencedirect.com/science/article/pii/S0168169911001220}, author = {J I Arribas and G V Sanchez-Ferrero and G Ruiz-Ruiz and Jaime Gomez-Gil} } @article {cordero2011unsupervised, title = {Unsupervised 4D myocardium segmentation with a Markov Random Field based deformable model}, journal = {Medical image analysis}, volume = {15}, number = {3}, year = {2011}, pages = {283{\textendash}301}, publisher = {Elsevier}, author = {Lucilio Cordero-Grande and Gonzalo Vegas-S{\'a}nchez-Ferrero and Pablo Casaseca-de-la-Higuera and Alberto San-Rom{\'a}n-Calvar, J and A. Revilla-Orodea and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {cardenes2010analysis, title = {Analysis of the pyramidal tract in tumor patients using diffusion tensor imaging}, journal = {NeuroImage}, volume = {50}, number = {1}, year = {2010}, pages = {27{\textendash}39}, publisher = {Elsevier}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Emma Mu{\~n}oz-Moreno and Sarabia-Herrero, Rosario and Rodr{\'\i}guez-Velasco, Margarita and Juan Jos{\'e} Fuertes-Alija and Marcos Martin-Fernandez} } @inbook {brun2009similar, title = {Similar Tensor Arrays{\textendash}A Framework for Storage of Tensor Array Data}, booktitle = {Tensors in Image Processing and Computer Vision}, year = {2009}, pages = {407{\textendash}428}, publisher = {Springer London}, organization = {Springer London}, author = {Brun, Anders and Marcos Martin-Fernandez and Acar, Burak and Emma Mu{\~n}oz-Moreno and Cammoun, Leila and Sigfridsson, Andreas and Dario Sosa-Cabrera and Svensson, Bj{\"o}rn and Herberthson, Magnus and Knutsson, Hans} } @article {casaseca2009multichannel, title = {A multichannel model-based methodology for extubation readiness decision of patients on weaning trials}, journal = {Biomedical Engineering, IEEE Transactions on}, volume = {56}, number = {7}, year = {2009}, pages = {1849{\textendash}1863}, publisher = {IEEE}, author = {Pablo Casaseca-de-la-Higuera and Federico Simmross-Wattenberg and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {san2008efficient, title = {Efficient tracking of MR tensor fields using a multilayer neural network}, journal = {IAENG International Journal of Computer Science}, volume = {35}, number = {1}, year = {2008}, pages = {129{\textendash}139}, author = {Luis Miguel San-Jose-Revuelta and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @proceedings {san2008ga, title = {A GA-based Approach for Parameter Estimation in DT-MRI Tracking Algorithms}, volume = {1}, year = {2008}, author = {Luis Miguel San-Jose-Revuelta and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @proceedings {simmross2008modelling, title = {Modelling Network Traffic as alpha-Stable Stochastic Processes: An Approach Towards Anomaly Detection}, year = {2008}, pages = {25{\textendash}32}, author = {Federico Simmross-Wattenberg and Antonio Trist{\'a}n-Vega and Pablo Casaseca-de-la-Higuera and Juan Ignacio Asensio-P{\'e}rez and Marcos Martin-Fernandez and Yannis A Dimitriadis and Carlos Alberola-Lopez} } @article {aja2008restoration, title = {Restoration of DWI data using a Rician LMMSE estimator}, journal = {Medical Imaging, IEEE Transactions on}, volume = {27}, number = {10}, year = {2008}, pages = {1389{\textendash}1403}, publisher = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Niethammer, Marc and Kubicki, Marek and Martha E Shenton and Carl-Fredik Westin} } @proceedings {sosa2008strain, title = {Strain index: a new visualizing parameter for US elastography}, year = {2008}, pages = {69200W{\textendash}69200W}, publisher = {International Society for Optics and Photonics}, author = {Dario Sosa-Cabrera and Rodrigo de Luis-Garc{\'\i}a and Antonio Trist{\'a}n-Vega and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @proceedings {sosa2008strain, title = {Strain index: a new visualizing parameter for US elastography}, volume = {6920}, year = {2008}, pages = {6920}, publisher = {International Society for Optical Engineering; 1999}, author = {Dario Sosa-Cabrera and Rodrigo de Luis-Garc{\'\i}a and Antonio Trist{\'a}n-Vega and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @proceedings {433, title = {On the estimation of joint probability density functions for multi-modal registration of medical images}, volume = {26}, year = {2008}, pages = {13-16}, publisher = {Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, address = {Valladolid, Spain}, author = {Antonio Trist{\'a}n-Vega and Federico Simmross-Wattenberg and Emma Mu{\~n}oz-Moreno and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez} } @conference {san2007neural, title = {Neural Network-Assisted Fiber Tracking of Synthetic and White Matter DT-MR Images.}, booktitle = {World Congress on Engineering}, year = {2007}, pages = {618{\textendash}623}, author = {Luis Miguel San-Jose-Revuelta and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @inbook {niethammer2007outlier, title = {Outlier rejection for diffusion weighted imaging}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2007}, year = {2007}, pages = {161{\textendash}168}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Niethammer, Marc and Bouix, Sylvain and Santiago Aja-Fern{\'a}ndez and Carl-Fredik Westin and Martha E Shenton} } @conference {479, title = {Ultrasound Based Intraoperative Brain Shift Correction}, booktitle = {Ultrasonics Symposium, 2007. IEEE}, year = {2007}, publisher = {IEEE}, organization = {IEEE}, author = {Gonz{\'a}lez, Javier and Dario Sosa-Cabrera and Ortega, Mario and Gil, Jose Antonio and Antonio Trist{\'a}n-Vega and Emma Mu{\~n}oz-Moreno and Rodrigo de Luis-Garc{\'\i}a} } @article {bouix2007evaluating, title = {On evaluating brain tissue classifiers without a ground truth}, journal = {Neuroimage}, volume = {36}, number = {4}, year = {2007}, pages = {1207{\textendash}1224}, publisher = {Academic Press}, author = {Bouix, Sylvain and Marcos Martin-Fernandez and Ungar, Lida and Nakamura, Motoaki and Koo, Min-Seong and McCarley, Robert W and Martha E Shenton} } @conference {san2007new, title = {A new proposal for 3D fiber tracking in synthetic diffusion tensor magnetic resonance images}, booktitle = {Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on}, year = {2007}, pages = {1{\textendash}4}, publisher = {IEEE}, organization = {IEEE}, author = {Luis Miguel San-Jose-Revuelta and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @inbook {418, title = {A statistical-genetic algorithm to select the most significant features in mammograms}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {4673 LNCS}, year = {2007}, pages = {189-196}, abstract = {

An automatic classification system into either malignant or benign microcalcification from mammograms is a helpful tool in breast cancer diagnosis. From a set of extracted features, a classifying method using neural networks can provide a probability estimation that can help the radiologist in his diagnosis. With this objective in mind, this paper proposes a feature selection algorithm from a massive number of features based on a statistical distance method in conjunction with a genetic algorithm (GA). The use of a statistical distance as optimality criterion was improved with genetic algorithms for selecting an appropriate subset of features, thus making this algorithm capable of performing feature selection from a massive set of initial features. Additionally, it provides a criterion to select an appropriate number of features to be employed. Experimental work was performed using Generalized Softmax Perceptrons (GSP), trained with a Strict Sense Bayesian cost function for direct probability estimation, as microcalcification classifiers. A Posterior Probability Model Selection (PPMS) algorithm was employed to determine the network complexity. Results showed that this algorithm converges into a subset of features which has a good classification rate and Area Under Curve (AUC) of the Receiver Operating Curve (ROC). {\^A}{\textcopyright} Springer-Verlag Berlin Heidelberg 2007.

}, keywords = {Breast cancer, Diagnosis, Feature extraction, Genetic algorithms, Mammography, Microcalcification classification, Network complexity, Neural network classifiers, Neural networks, Tumors}, isbn = {9783540742715}, issn = {03029743}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-38149142403\&partnerID=40\&md5=ef139db3a0e5d603c4f721316abdcf2c}, author = {G V Sanchez-Ferrero and J I Arribas} } @proceedings {aja2006image, title = {Image quality assessment based on local variance}, year = {2006}, pages = {4815{\textendash}4818}, author = {Santiago Aja-Fern{\'a}ndez and Raul San Jose-Estepar and Carlos Alberola-Lopez and Carl-Fredik Westin} } @proceedings {san2006new, title = {A new method for fiber tractography in diffusion tensor magnetic resonance images}, volume = {6}, year = {2006}, pages = {380{\textendash}385}, author = {Luis Miguel San-Jose-Revuelta and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {palacios2005group, title = {Group-Slicer: A collaborative extension of 3D-Slicer}, journal = {Journal of Biomedical Informatics}, volume = {38}, year = {2005}, pages = {431{\textendash}442}, author = {Federico Simmross-Wattenberg and Palacios-Camarero, Cristina and Pablo Casaseca-de-la-Higuera and Miguel Angel Martin-Fernandez and Santiago Aja-Fern{\'a}ndez and Juan Ruiz-Alzola and Carl-Fredik Westin and Carlos Alberola-Lopez} } @inbook {ruiz2005landmark, title = {Landmark-Based Registration of Medical-Image Data}, booktitle = {Medical Image Analysis Methods, Edited by Lena Costaridou, CRC Press}, year = {2005}, author = {Juan Ruiz-Alzola and Suarez-Santana, E and Carlos Alberola-Lopez and Carl-Fredik Westin} } @conference {de2005pull, title = {Pull-Push Level Sets: A new term to encode prior knowledge for the segmentation of teeth images}, booktitle = {Medical Imaging}, year = {2005}, pages = {598{\textendash}605}, publisher = {International Society for Optics and Photonics}, organization = {International Society for Optics and Photonics}, author = {Rodrigo de Luis-Garc{\'\i}a and Raul San Jose-Estepar and Carlos Alberola-Lopez} } @inbook {martin2005two, title = {Two methods for validating brain tissue classifiers}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2005}, year = {2005}, pages = {515{\textendash}522}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Marcos Martin-Fernandez and Bouix, Sylvain and Ungar, Lida and McCarley, Robert W and Martha E Shenton} } @conference {429, title = {Weaning from mechanical ventilation: feature extraction from a statistical signal processing viewpoint}, booktitle = {Proc. 13th Signal Processing Conf., EUSIPCO}, year = {2005}, author = {Pablo Casaseca-de-la-Higuera and Rodrigo de Luis-Garc{\'\i}a and Federico Simmross-Wattenberg and Carlos Alberola-Lopez} } @conference {430, title = {A lossless compression algorithm based on predictive coding for volumetric medical datasets}, booktitle = {Proc. EUSIPCO 2005}, year = {2005}, author = {D{\'\i}ez-Garc{\'\i}a, M{\'o}nica and Federico Simmross-Wattenberg and Carlos Alberola-Lopez} } @conference {428, title = {The opportunity of grid services for CSCL-application development}, booktitle = {Parallel, Distributed and Network-Based Processing, 2005. PDP 2005. 13th Euromicro Conference on}, year = {2005}, publisher = {IEEE}, organization = {IEEE}, address = {Lausanne, Switzerland}, author = {Vaquero-Gonz{\'a}lez, Luis M and Hern{\'a}ndez-Leo, D and Federico Simmross-Wattenberg and Bote-Lorenzo, Miguel L and Juan Ignacio Asensio-P{\'e}rez and Yannis A Dimitriadis and G{\'o}mez-S{\'a}nchez, Eduardo and Vega-Gorgojo, Guillermo} } @inbook {jose2003lncs, title = {Freehand Ultrasound Reconstruction Based on ROI Prior Modeling and Normalized Convolution}, booktitle = {Lecture Notes in Computer Science}, volume = {2879}, year = {2003}, pages = {382{\textendash}390}, publisher = {Berlin: Springer-Verlag, 1973-}, organization = {Berlin: Springer-Verlag, 1973-}, author = {Raul San Jose-Estepar and Marcos Martin-Fernandez and Carlos Alberola-Lopez and Ellsmere, James and Kikinis, Ron and Carl-Fredik Westin} } @inbook {jose2003freehand, title = {Freehand Ultrasound Reconstruction Based on ROI Prior Modeling and Normalized Convolution}, booktitle = {Lecture Notes in Computer Science}, volume = {2879}, year = {2003}, pages = {382{\textendash}390}, publisher = {Berlin: Springer-Verlag, 1973-}, organization = {Berlin: Springer-Verlag, 1973-}, author = {Raul San Jose-Estepar and Marcos Martin-Fernandez and Carlos Alberola-Lopez and Ellsmere, James and Kikinis, Ron and Carl-Fredik Westin} } @inbook {ruiz2003geostatistical, title = {Geostatistical medical image registration}, booktitle = {Medical Image Computing and Computer-Assisted Intervention-MICCAI 2003}, year = {2003}, pages = {894{\textendash}901}, publisher = {Springer}, organization = {Springer}, author = {Juan Ruiz-Alzola and Suarez, Eduardo and Carlos Alberola-Lopez and Warfield, Simon K and Carl-Fredik Westin} } @inbook {martin2003novel, title = {A novel Gauss-Markov random field approach for regularization of diffusion tensor maps}, booktitle = {Computer Aided Systems Theory-EUROCAST 2003}, year = {2003}, pages = {506{\textendash}517}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Marcos Martin-Fernandez and Raul San Jose-Estepar and Carl-Fredik Westin and Carlos Alberola-Lopez} } @article {san2003theoretical, title = {A theoretical framework to three-dimensional ultrasound reconstruction from irregularly sampled data}, journal = {Ultrasound in medicine \& biology}, volume = {29}, number = {2}, year = {2003}, pages = {255{\textendash}269}, publisher = {Elsevier}, author = {Raul San Jose-Estepar and Marcos Martin-Fernandez and Caballero-Mart{\'\i}nez, P Pablo and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @conference {martin2001maximum, title = {Maximum likelihood contour estimation using beta-statistics in ultrasound images}, booktitle = {Image and Signal Processing and Analysis, 2001. ISPA 2001. Proceedings of the 2nd International Symposium on}, year = {2001}, pages = {207{\textendash}212}, publisher = {IEEE}, organization = {IEEE}, author = {Marcos Martin-Fernandez and Raul San Jose-Estepar and Carlos Alberola-Lopez} } @conference {san2001reshaping, title = {Reshaping polygonal meshes with smoothed normals extracted from ultrasound volume data: An optimization approach}, booktitle = {Medical Imaging 2001}, year = {2001}, pages = {462{\textendash}472}, publisher = {International Society for Optics and Photonics}, organization = {International Society for Optics and Photonics}, author = {Raul San Jose-Estepar and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @conference {estepar2000kalman, title = {Kalman filter technique applied to surface reconstruction and visualization from noisy volume data}, booktitle = {Medical Imaging 2000}, year = {2000}, pages = {396{\textendash}407}, publisher = {International Society for Optics and Photonics}, organization = {International Society for Optics and Photonics}, author = {Raul San Jose-Estepar and Rivera, Alberto and Pinacho, Marco and Carlos Alberola-Lopez and Juan Ruiz-Alzola} }