Predicting clinically significant prostate cancer with a deep learning approach: a multicentre retrospective study

被引：0
作者：
Litao Zhao
Jie Bao
Xiaomeng Qiao
Pengfei Jin
Yanting Ji
Zhenkai Li
Ji Zhang
Yueting Su
Libiao Ji
Junkang Shen
Yueyue Zhang
Lei Niu
Wanfang Xie
Chunhong Hu
Hailin Shen
Ximing Wang
Jiangang Liu
Jie Tian
机构：
[1] Beihang University,School of Engineering Medicine
[2] Key Laboratory of Big Data-Based Precision Medicine (Beihang University),School of Biological Science and Medical Engineering
[3] Ministry of Industry and Information Technology of China,Department of Radiology
[4] Beihang University,Department of Radiology
[5] The First Affiliated Hospital of Soochow University,Department of Radiology
[6] The Affiliated Zhangjiagang Hospital of Soochow University,Department of Radiology
[7] Suzhou Kowloon Hospital,Department of Radiology
[8] Shanghai Jiaotong University School of Medicine,Department of Radiology
[9] The People’s Hospital of Taizhou,Department of Radiology
[10] Changshu No.1 People’s Hospital,undefined
[11] The Second Affiliated Hospital of Soochow University,undefined
[12] The People’s Hospital of Suqian,undefined
来源：
European Journal of Nuclear Medicine and Molecular Imaging | 2023年 / 50卷
关键词：
Magnetic resonance imaging; PI-RADS; Deep learning; Clinically significant prostate cancer;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：727 / 741
页数：14
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