Noise Estimation in Magnetic Resonance SENSE Reconstructed Data (EMBC 2013)

Poster presented at EMBC 2013 (Osaka)

Abstract: Parallel imaging methods allow to increase the acquisition rate via subsampled acquisitions of the {\bf k}-space. SENSE reconstruction process yields to a variance of noise value which is dependent on the position within the image. Hence, the traditional noise estimation methods based on a single noise level for the whole image fail. Accordingly, we propose a novel method to recover the complete spatial pattern of the variance of noise in SENSE reconstructed images up from the sensitivity maps of each receiver coil. Our method fits applications in statistical image processing tasks such as image denoising.