Abstract: A vector-based active contour model algorithm for corpus callosum segmentation on diffusion tensor images was proposed. It utilized the vector-based Chan-Vese model to construct a vector-based signed pressure force function that controls the direction of the evolution. The form of the vector norm was used to describe anisotropy characteristics of corpus callosum on diffusion tensor images. The vector-based active contour model with both the global and the local segmentation property was also introduced into this algorithm. Segmentation results of 10 real diffusion tensor images showed that the proposed algorithm could segment corpus callosum precisely and stably.

Key words: Diffusion tensor imaging, Brain corpus callosum segmentation, Gray mapping, Vector active contour model