Full convolutional network based multiple side-output fusion architecture for the segmentation of rectal tumors in magnetic resonance images: A multi-vendor study.

Abstract

Authors

• Mengmeng Wang
  Department of General Medicine, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, 046000, China. wangtygqsf@sina.com.
• Peiyi Xie
  Department of Radiology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510655, China.
• Zhao Ran
  University of Science and Technology of China, Hefei, Anhui, 230026, China.
• Junming Jian
  University of Science and Technology of China, Hefei, Anhui, 230026, China.
• Rui Zhang
  Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
• Wei Xia
  Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
• Tao Yu
  Department of Smart Experience Design Kookmin University, Seoul 02707, Republic of Korea.
• Caifeng Ni
  The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215006, China.
• Jinhui Gu
  Chinese Academy of Traditional Chinese Medicine, Beijing, 100700, China.
• Xin Gao
  Department of Computer Science, New Jersey Institute of Technology, Newark, New Jersey, USA.
• Xiaochun Meng
  Department of Radiology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510655, China.

Keywords

External Resources