3D segmentation of rodent brains using deformable models and variational methods

Abstract

3D functional segmentation of brain images is important in understating the relationships between anatomy and mental diseases in brains. Volumetric analysis of various brain structures such as the cerebellum plays a critical role in studying the structural changes in brain regions as a function of development, trauma, or neurodegeneration. Although various segmentation methods in clinical studies have been proposed, many of them require a priori knowledge about the locations of the structures of interest, which prevents the fully automatic segmentation. Besides, the topological changes of structures are difficult to detect. In this paper, we present a novel method for detecting and locating the brain structures of interest that can be used for the fully automatic 3D functional segmentation of rodent brain MR images. The presented method is based on active shape model (ASM), Metamorph models and variational techniques. It focuses on detecting the topological changes of brain structures based on a novel volume ratio criteria. The mean successful rate of the topological change detection shows 86.6% accuracy compared to the expert identified ground truth.