Gao, Wenpeng, Chen, Xiaoguang, Fu, Yili, and Zhu, Minwei
Computational and Mathematical Methods in Medicine. Annual, 2018, Vol. 2018
Magnetic resonance imaging -- Analysis and Magnetic resonance imaging -- Models
1. Introduction The corpus callosum (CC) is the main commissural bundle of fibers interconnecting the left and right cerebral hemispheres . It facilitates interhemispheric communication in the human brain. Its [...] The centerline, as a simple and compact representation of object shape, has been used to analyze variations of the human callosal shape. However, automatic extraction of the callosal centerline remains a sophisticated problem. In this paper, we propose a method of automatic extraction of the callosal centerline from segmented mid-sagittal magnetic resonance (MR) images. A model- based point matching method is introduced to localize the anterior and posterior endpoints of the centerline. The model of the endpoint is constructed with a statistical descriptor of the shape context. Active contour modeling is adopted to drive the curve with the fixed endpoints to approximate the centerline using the gradient of the distance map of the segmented corpus callosum. Experiments with 80 segmented mid-sagittal MR images were performed. The proposed method is compared with a skeletonization method and an interactive method in terms of recovery error and reproducibility. Results indicate that the proposed method outperforms skeletonization and is comparable with and sometimes better than the interactive method.