Self-supervised learning enables 3D digital subtraction angiography reconstruction from ultra-sparse 2D projection views: A multicenter study-Reference-Cited by-同舟云学术

Self-supervised learning enables 3D digital subtraction angiography reconstruction from ultra-sparse 2D projection views: A multicenter study

Published:2022-10 Issue:10 Volume:3 Page:100775
ISSN:2666-3791
Container-title:Cell Reports Medicine
language:en
Short-container-title:Cell Reports Medicine

Author:

Zhao Huangxuan,Zhou Zhenghong,Wu Feihong,Xiang Dongqiao,Zhao Hui,Zhang Wei,Li Lin,Li Zhong,Huang Jia,Hu Hongyao,Liu Chengbo,Wang Tao,Liu Wenyu,Ma Jinqiang,Yang Fan,Wang Xinggang,Zheng Chuansheng^ORCID

Funder

China Postdoctoral Science Foundation

Key Research and Development Program of Hunan Province of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

General Biochemistry, Genetics and Molecular Biology

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