Brain MRI T1-Map and T1-weighted image segmentation in a variational framework
In this paper we propose a constrained version of Mumford-Shah'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 flavor 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 T1-Maps and also by two simulated brains of T1-weighted data from the BrainWeb[3] public database.