@article {899,
	title = {Apparent propagator anisotropy from single-shell diffusion MRI acquisitions},
	journal = {Magnetic Resonance in Medicine},
	volume = {85},
	year = {2021},
	month = {2021},
	pages = {2869-2881},
	chapter = {2869},
	doi = {https://doi.org/10.1002/mrm.28620},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/mrm.28620},
	author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Derek K. Jones}
}
@proceedings {856,
	title = {AMURA with standard single-shell acquisition can detect changes beyond the Diffusion Tensor: a migraine clinical study},
	volume = {4549},
	year = {2020},
	month = {2020},
	abstract = {AMURA (Apparent Measures Using Reduced Acquisitions) is an alternative formulation to drastically reduce the number of samples needed for the estimation of diffusion properties related to the Ensemble Average diffusion Propagator (EAP). Although these measures were initially intended for medium-to-high b-values, in this work we evaluate their performance in DTI-like acquisitions. Fifty healthy controls, 54 episodic migraine (EM) and 56 chronic migraine (CM) patients were compared, using a single-shell diffusion scheme at b=1000 s/mm2. We compare AMURA measures (return-to-origin, return-to-axis and return-to-plane probabilities) to traditional DTI measures. Differences between EM and controls were only detectable using the return-to-origin probability.},
	author = {{\'A}lvaro Planchuelo-G{\'o}mez and Rodrigo de Luis-Garc{\'\i}a and Antonio Trist{\'a}n-Vega and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}ngel L. Guerrero and Santiago Aja-Fern{\'a}ndez}
}
@inbook {895,
	title = {Alternative Diffusion Anisotropy Metric from Reduced MRI Acquisitions},
	booktitle = {Computational Diffusion MRI},
	year = {2020},
	pages = {13{\textendash}24},
	publisher = {Springer, Cham},
	organization = {Springer, Cham},
	author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Rodrigo de Luis-Garc{\'\i}a and Derek K. Jones}
}
@article {627,
	title = {Adjugate Diffusion Tensors for Geodesic Tractography in White Matter},
	journal = {Journal of Mathematical Imaging and Vision},
	volume = {54},
	year = {2015},
	pages = {1{\textendash}14},
	abstract = {<p>One of the approaches in diffusion tensor imaging is to consider a Riemannian metric given by the inverse diffusion tensor. Such a metric is used for geodesic tractography and connectivity analysis in white matter. We propose a metric tensor given by the adjugate rather than the previously proposed inverse diffusion tensor. The adjugate metric can also be employed in the sharpening framework. Tractography experiments on synthetic and real brain diffusion data show improvement for high-curvature tracts and in the vicinity of isotropic diffusion regions relative to most results for inverse (sharpened) diffusion tensors, and especially on real data. In addition, adjugate tensors are shown to be more robust to noise.</p>
},
	issn = {1573-7683},
	doi = {10.1007/s10851-015-0586-8},
	url = {http://dx.doi.org/10.1007/s10851-015-0586-8},
	author = {Andrea Fuster and Tom Dela-Haije and Antonio Trist{\'a}n-Vega and Birgit Plantinga and Carl-Fredik Westin and Luc Florack}
}
@conference {vegas2013anisotropic,
	title = {Anisotropic diffusion filtering for correlated multiple-coil MRI},
	booktitle = {Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE},
	year = {2013},
	pages = {2956{\textendash}2959},
	publisher = {IEEE},
	organization = {IEEE},
	author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Gabriel Ramos-Llorden and Rodrigo de Luis-Garc{\'\i}a and Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez}
}
@conference {vegas2012anisotropic,
	title = {Anisotropic LMMSE denoising of MRI based on statistical tissue models},
	booktitle = {Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on},
	year = {2012},
	pages = {1519{\textendash}1522},
	publisher = {IEEE},
	organization = {IEEE},
	author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez and Cesar Palencia and Deriche, Rachid}
}
@article {aja2010background,
	title = {About the background distribution in MR data: a local variance study},
	journal = {Magnetic resonance imaging},
	volume = {28},
	number = {5},
	year = {2010},
	pages = {739{\textendash}752},
	publisher = {Elsevier},
	author = {Santiago Aja-Fern{\'a}ndez and Gonzalo Vegas-S{\'a}nchez-Ferrero and Antonio Trist{\'a}n-Vega}
}
