Fully automatic segmentation of the dentate nucleus using diffusion weighted images
We propose a fully automatic method to segment the dentate nucleus using diffusion weighted images (DWI). Initialization of the dentate nucleus is produced by combining the information from tractography results on the diffusion tensor images (reconstructed from DWI) and b0 images. A geometric de-formable model (GDM) with generalized gradient vector flow (GGVF) is then applied on the b0 image to generate the segmentation by evolving the level set function. Experiments have been carried out on real data and quantitative comparison shows that our segmentation results agree well with expert manual delineations and produce accurate results.