Automatic infant brain segmentation based on diffusion tensor imaging

VernacularTitle:基于扩散张量成像的婴幼儿大脑图像自动分割
Author: Lin WANG ; Gang YU
Keywords: Infant; Child; Magnetic resonance imaging; Diffusion tensor imaging; Brain segmentation
From: Chinese Journal of Medical Imaging Technology 2017;33(8):1264-1268
CountryChina
Language:Chinese
Abstract: Objective To investigate the feasibility and value of automatic segmentation of infant brain images based on diffusion tensor image (DTI).Methods A method of segmentation of infant brain based on DTI images was proposed.The method was mainly included two stages:①Extracting the cerebrospinal fluid (CSF) using the distribution of water;②Extracting the white matter (WM) adopting the anisotropic diffusion of water in neurons,followed by distinguishing the gray matter (GM) component.Results Through the feature selection method designed in this study,the effective DTI feature combination was selected.The first step was to extract CSF with mean diffusity (MD) and the third eigenvalue (L3),and the second step was to extract WM and GM with fractional anisotropy (FA) and the L3.The highest average similarity was obtained by the two steps.The two-step segmentation could be successfully performed in infant brain image segmentation and satisfied with the split effect.Conclusion The automatic segmentation of infant brain based on DTI in this study is reasonable and feasible,and has high segmentation accuracy.