Multi-spatial-attention U-Net: a novel framework for automated gallbladder segmentation on CT images.

Abstract

Authors

• Henan Lou
  Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
• Xiaobo Wen
  The Affiliated Hospital of Qingdao University, Qingdao Medical College, Qingdao University, Qingdao 266071, China.
• Fanxia Lin
  Department of Radiology, People's Hospital of Rizhao, Rizhao, China.
• Zhan Peng
  Department of Cardiovascular Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Vessel Disease, Beijing, People's Republic of China.
• Qiuxiao Wang
  Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao, China.
• Ruimei Ren
  Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao, China.
• Junlin Xu
  School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei 430065, China.
• Jinfei Fan
  Qingdao Cancer Institute, Qingdao University, Qingdao, China.
• Hao Song
  Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
• Xiaomeng Ji
  Department of Tourism, Management College, Ocean University of China, Qingdao, China.
• Huiyu Wang
  School of Control Science and Technology, Shandong University, Jinan 250061, PR China. Electronic address: huiyuwang001@163.com.
• Xiangyin Sun
  Department of Oncology, Qingdao Sixth People's Hospital, Qingdao, China.
• Yinying Dong
  Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao, China. dongyinyingwang@163.com.

Keywords

External Resources