Syn_SegNet: A Joint Deep Neural Network for Ultrahigh-Field 7T MRI Synthesis and Hippocampal Subfield Segmentation in Routine 3T MRI-Reference-Cited by-同舟云学术

Syn_SegNet: A Joint Deep Neural Network for Ultrahigh-Field 7T MRI Synthesis and Hippocampal Subfield Segmentation in Routine 3T MRI

Published:2023-10 Issue:10 Volume:27 Page:4866-4877
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Li Xinwei¹^ORCID,Wang Linjin¹^ORCID,Liu Hong¹,Ma Baoqiang²^ORCID,Chu Lei³^ORCID,Dong Xiaoxi³,Zeng Debin³^ORCID,Che Tongtong³,Jiang Xiaoming¹^ORCID,Wang Wei¹^ORCID,Hu Jun⁴^ORCID,Li Shuyu⁵^ORCID

Affiliation:

1. School of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing, China

2. Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands

3. School of Biological Science Medical Engineering, Beihang University, Beijing, China

4. Department of Neurology, Southwest Hospital, Army Medical University, Chongqing, China

5. State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China

Funder

National Natural Science Foundation of China

National Science and Technology Innovation 2030 Major Program

Startup Funds for Talents at Beijing Normal University

Key Project of Technology Innovation and Application Development of Chongqing

China Postdoctoral Science Foundation

Chongqing Postdoctoral Science Special Foundation

Youth Innovation Promotion Association of the Chinese Academy of Sciences

Ministry of Science and Technology of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10272722/10218394.pdf?arnumber=10218394

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