Analysis and segmentation of Brain MR images with Blind-Source-Separation techniques

The intensity value of each voxel in a brain MR image is considered to be a linear combination of signal intensities emitted from protons in aqueous and lipid environments inside that voxel. A novel model describing the proton density (PD) and fraction of protons in aqueous environment (Water Fraction - WF) as independent sources of an MR image is suggested. We consider an input set of registered T₁ and T₂ weighted images to be the mixtures. The sources are separated from these mixtures by applying a geometrical blind-source-separation technique on sparse projection of the mixtures. A novel model is proposed to relate between the observed scatter-plot and the actual orientations of the mixing matrix and its estimation. The resulting PD source-image is compared to available PD weighted image of the same patient. WF image is used for anatomic classification of the image into brain tissues - White Matter (WM), Grey Matter (GM), and Cerebrospinal Fluid (CSF).