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Published at November 21Enhancing Diagnostic Precision in Gastric Bleeding through Automated Lesion Segmentation: A Deep DuS-KFCM Approach
Released Date: November 21, 2024
Authors: Xian-Xian Liu1, Mingkun Xu2, Yuanyuan Wei3, Huafeng Qin4, Qun Song5, Simon Fong1, Feng Tien6, Wei Luo7, Juntao Gao8, Zhihua Zhang9, Shirley Siu10
Aff.: 1The Department of Computer and Information Science, University of Macau, Macau SAR, 999078, China; 2Guangdong Institute of Intelligence Science and Technology, Zhuhai, 519031, China; 3Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, 999077, Hong Kong SAR, China; 4The School of Computer Science and Information Engineering, Chongqing Technology and Business University, Chongqing, 400067, China; 5Institute of Artificial Intelligence, Chongqing Technology and Business University, Chongqing, 400067, China; 6Hebei Key Laboratory of Medical Data Science, Institute of Biomedical Informatics, School of Medicine, Hebei University of Engineering, Handan, Hebei Province, 056038, China; 7The director of the Institute of Clinical Medicine, The First People's Hospital of Foshan, Guangzhou, 510060, China; 8The Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, California, China; 9Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China; 10Centre for Artificial Intelligence Driven Drug Discovery, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, Macau, 999078, China
