Segmentation of Brain MRI

Effective, precise and consistent brain cortical tissue segmentation from magnetic resonance (MR) images is one of the most prominent issues in many applications of medical image processing. These applications include surgical planning (Kikinis et al., 1996), surgery navigation (Grimson et al., 1997), multimodality image registration (Saeed, 1998), abnormality detection (Rusinek et al., 1991), multiple sclerosis lesion quantification (Udupa et al., 1997), brain tumour detection (Vaidyanathan et al., 1997), functional mapping (Roland et al., 1993), etc. Traditionally, the purpose of segmentation is to partition the image into non-overlapping, constituent regions (or called classes, clusters, subsets or sub-regions) that are homogeneous with respect to intensity and texture (Gonzalez & Woods, 1992). If the domain of the image is given by 硬, then the segmentation problem is to determine the sets 鯨賃 ⊂ 硬, whose union is the entire domain 硬. Thus, the sets that make up a segmentation must satisfy