Fast learning of fiber orientation distribution function for MR tractography using convolutional neural network

• Published in: Medical physics (Lancaster) Vol. 46; no. 7; pp. 3101 - 3116
• Main Authors: Lin, Zhichao, Gong, Ting, Wang, Kewen, Li, Zhiwei, He, Hongjian, Tong, Qiqi, Yu, Feng, Zhong, Jianhui
• Format: Journal Article
• Language: English
• Published: United States 01.07.2019
• Subjects: constrained spherical deconvolution; convolutional neural network; Deep Learning; Diffusion Tensor Imaging; diffusion‐weighted MR imaging; fiber orientation dispersion function; fiber tractography; Image Processing, Computer-Assisted - methods; Time Factors; diffusion-weighted MR imaging; convolutional neural network; constrained spherical deconvolution; fiber orientation dispersion function; fiber tractography

Purpose In diffusion‐weighted magnetic resonance imaging (DW‐MRI), the fiber orientation distribution function (fODF) is of great importance for solving complex fiber configurations to achieve reliable tractography throughout the brain, which ultimately facilitates the understanding of brain connect...