Fully automated segmentation and volumetric measurement of ocular adnexal lymphoma by deep learning-based self-configuring nnU-net on multi-sequence MRI: a multi-center study.

Abstract

Authors

• Guorong Wang
  Department of Radiology, Beijing Tongren Hospital, Capital Medical University, No.1 DongJiaoMinXiang Street, DongCheng District, Beijing, 100730, China.
• Bingbing Yang
  Department of Radiology, Beijing Tongren Hospital, Capital Medical University, No.1 DongJiaoMinXiang Street, DongCheng District, Beijing, 100730, China.
• Xiaoxia Qu
  Department of Radiology, Beijing Tongren Hospital, Capital Medical University, No. 1 Dongjiaominxiang Street, Dongcheng District, Beijing, 100730, China; Clinical Center for Eye Tumors, Capital Medical University, Beijing, 100730, China.
• Jian Guo
  Department of Radiology, Beijing Tongren Hospital, Capital Medical University, No. 1 Dongjiaominxiang Street, Dongcheng District, Beijing, 100730, China; Clinical Center for Eye Tumors, Capital Medical University, Beijing, 100730, China.
• Yongheng Luo
  Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China.
• Xiaoquan Xu
  Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
• Feiyun Wu
  Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
• Xiaoxue Fan
  Division of Biomedical Engineering, China Medical University, China.
• Yang Hou
  Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China.
• Song Tian
  Infervision, Beijing, China.
• Sicong Huang
• Junfang Xian
  Department of Radiology, Beijing Tongren Hospital, Capital Medical University, No. 1 Dongjiaominxiang Street, Dongcheng District, Beijing, 100730, China; Clinical Center for Eye Tumors, Capital Medical University, Beijing, 100730, China. Electronic address: cjr.xianjunfang@vip.163.com.

Keywords

External Resources