Feihong Liu1,2, Junwei Yang2,3, Zhiming Cui2,4, Xiaowei He1,5, Jun Feng1,5, and Dinggang Shen2,6,7
1School of Information Science and Technology, Northwest University, Xi'an, China, 2School of Biomedical Engineering, ShanghaiTech University, Shanghai, China, 3Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom, 4Department of Computer Science, The University of Hong Kong, Hong Kong, China, 5State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Services, Xi'an, China, 6Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China, 7Department of Artificial Intelligence, Korea University, Seoul, Korea, Republic of
1School of Information Science and Technology, Northwest University, Xi'an, China, 2School of Biomedical Engineering, ShanghaiTech University, Shanghai, China, 3Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom, 4Department of Computer Science, The University of Hong Kong, Hong Kong, China, 5State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Services, Xi'an, China, 6Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China, 7Department of Artificial Intelligence, Korea University, Seoul, Korea, Republic of
We calibrated the phase correction procedures with the goal of unbiased white matter microstructure estimation.
`FA maps new' denotes the phase correction results obtained by the renewed procedures. Artifacts are significantly eliminated for all three methods, while the FA values in corpus callosum is increased properly.
`TV new', `CF new', and `MPPCA new' denote the phase correction results obtained by the renewed procedures. The renewed procedures yield more accurate FA values, especially for MPPCA. Black color of white matter means high accuracy achieved. MAG denotes the magnitude images.