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AI-based strategies in breast mass ≤ 2 cm classification with mammography and tomosynthesis.

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作者: Zhenzhen,Shao [1] ; Yuxin,Cai [2] ; Yujuan,Hao [3] ; Congyi,Hu [4] ; Ziling,Yu [5] ; Yue,Shen [6] ; Fei,Gao [7] ; Fandong,Zhang [8] ; Wenjuan,Ma [9] ; Qian,Zhou [10] ; Jingjing,Chen [11] ; Hong,Lu [12]
作者单位: Department of Breast Imaging, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, PR China. Electronic address: shaozhenzhen726@163.com. [1] Department of Breast Imaging, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, PR China. Electronic address: 977052259@qq.com. [2] Department of Breast Imaging, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, PR China. Electronic address: hao_yj2009@sina.com. [3] Department of Breast Imaging, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, PR China. Electronic address: hucongyi1987@sina.com. [4] Department of Breast Imaging, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, PR China. Electronic address: ziling113@163.com. [5] Department of Breast Imaging, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, PR China. Electronic address: 2606589247@qq.com. [6] School of Computer Science, Peking University, Beijing, PR China. Electronic address: fei.gao@pku.edu.com. [7] Deepwise AI Lab, Beijing, PR China. Electronic address: zhangfandong@deepwise.com. [8] Department of Breast Imaging, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, PR China. Electronic address: mawenjuan2008@163.com. [9] Department of Breast imaging, The affiliated Hospital of Qingdao University, Qingdao, PR China. Electronic address: 15315000096@139.com. [10] Department of Breast imaging, The affiliated Hospital of Qingdao University, Qingdao, PR China. Electronic address: chengjingjingsky@qdu.com. [11] Department of Breast Imaging, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, PR China. Electronic address: honglu@tmu.edu.cn. [12]
DOI 10.1016/j.breast.2024.103805
PMID 39321503
发布时间 2024-11-21
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