Deep Learning Based on MR Imaging for Predicting Outcome of Uterine Fibroid Embolization.

Abstract

Authors

• Yong-Heng Luo
  Department of Radiology, The Second Xiangya Hospital of Central South University, 139 Renming Middle Road, Changsha, Hunan, China.
• Ianto Lin Xi
  Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.
• Robin Wang
  Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.
• Hatem Omar Abdallah
  Division of Interventional Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
• Jing Wu
  School of Pharmaceutical Science, Jiangnan University, Wuxi, 214122, Jiangsu, China.
• Ansar Z Vance
  Division of Interventional Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
• Ken Chang
  Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts.
• Maureen Kohi
  Department of Radiology and Biomedical Imaging, University of California, San Francisco, California.
• Lisa Jones
  Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
• Shilpa Reddy
  Division of Interventional Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
• Zi-Shu Zhang
  Department of Radiology, The Second Xiangya Hospital of Central South University, 139 Renming Middle Road, Changsha, Hunan, China. Electronic address: zishuzhang@csu.edu.cn.
• Harrison X Bai
  Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
• Richard Shlansky-Goldberg
  Division of Interventional Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.

Keywords

External Resources