Brain MRI T1-Map and T1-weighted image segmentation in a variational framework

In this paper we propose a constrained version of MumfordShah’s[1] segmentationwith an information-theoretic point of view[2] in order to devise a systematic procedure to segment brain MRI data for two modalities of parametric T1-Map and T1-weighted images in both 2-D and 3-D settings. The incorporation of a tuning weight in particular adds a probabilistic avor to our segmentation method, and makes the three-tissue segmentation possible. Our method uses region based active contours which have proven to be robust. The method is validated by two real objects which were used to generate T1Maps and also by two simulated brains of T1-weighted data from the BrainWeb[3] public database.