SERR-U-Net: Squeeze-and-Excitation Residual and Recurrent Block-Based U-Net for Automatic Vessel Segmentation in Retinal Image

被引：0
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作者：
Wang, Jinke [1 ,2 ]
Li, Xiang [1 ]
Lv, Peiqing [2 ]
Shi, Changfa [3 ]
机构：
[1] Rongcheng College, Harbin University of Science and Technology, Rongcheng,264300, China
[2] School of Automation, Harbin University of Science and Technology, Harbin,150080, China
[3] Mobile E-Business Collaborative Innovation Center of Hunan Province, Hunan University of Technology and Business, Changsha,410205, China
来源：
Computational and Mathematical Methods in Medicine | 2021年 / 2021卷
关键词：
This work was supported in part by the National Natural Science Foundation of China (Nos. 61701178; 71972069; 61471170; and; 61976088); the Heilongjiang Provincial Natural Science Foundation of China (No. LH2019F023); the Fundamental Research Foundation for Universities of Heilongjiang Province (No. LGYC2018JQ004); the Hunan Provincial Natural Science Foundation of China (Nos. 2018JJ3256 and 2019JJ152); the Research Foundation of Education Bureau of Hunan Province (Nos. 19B309 and 18A307); and the Science Technology Innovation Team on Logistics SystemOptimization and Operation Management of Hunan Provincial Universities;
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摘要：
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