Volumetric segmentation via 3D active shape models

A volumetric image segmentation algorithm has been developed and implemented by extending a 2D algorithm based on active shape models. The new technique allows segmentation of 3D objects that are embedded within volumetric image data. The extension from 2D involved four components: landmarking, shape modeling, gray-level modeling, and segmentation. Algorithms and software tools have been implemented to allow a user to efficiently landmark a 3D object training set. Additional tools were built that subsequently,, generate models of 3D object shape and gray-level appearance based on this training data. An object segmentation strategy was implemented that optimizes these models to segment a previously unseen instance of the object. Results of this new 3D segmentation algorithm have been generated for a synthetic volumetric data set