Predicting microvascular invasion in hepatocellular carcinoma with a CT- and MRI-based multimodal deep learning model.

Abstract

Authors

• Yan Lei
  School of General Quality Education, Wuchang University of Technology, Wuhan, China.
• Bao Feng
  The Department of Radiology, Jiangmen Central Hospital/Affiliated Jiangmen Hospital of Sun Yat-Sen University, No. 23 Haibang Street, Jiangmen, 529000, Guangdong, China.
• Meiqi Wan
  Department of Radiology, Jiangmen Central Hospital, 23 Beijie Haibang Street, Jiangmen, People's Republic of China.
• Kuncai Xu
  Laboratory of Artificial Intelligence of Biomedicine, Guilin University of Aerospace Technology, Guilin, Guangxi Province, 541004, People's Republic of China.
• Jin Cui
  Department of Radiology, Jiangmen Central Hospital, 23 Beijie Haibang Street, Jiangmen 529030, PR China.
• Changyi Ma
  Department of Radiology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of Guangdong Medical University, Affiliated Jiangmen Hospital of SUN YAT-SEN University, 23 Beijie Haibang Street, Jiangmen, 529030, China.
• Junqi Sun
  Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York.
• Changyin Yao
  Department of Radiology, Jiangmen Central Hospital, 23 Beijie Haibang Street, Jiangmen, People's Republic of China.
• Shiman Gan
  Department of Radiology, Jiangmen Central Hospital, 23 Beijie Haibang Street, Jiangmen, People's Republic of China.
• Jiangfeng Shi
  School of Automation Science and Engineering, South China University of Technology, Guangzhou, China.
• Enming Cui
  Department of Radiology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of Guangdong Medical University, Affiliated Jiangmen Hospital of SUN YAT-SEN University, 23 Beijie Haibang Street, Jiangmen, 529030, China. Electronic address: cem2008@163.com.

Keywords

External Resources