Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer.

Abstract

Authors

• Yu-Chun Lin
  Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Linkou, Chang Gung University, Taoyuan, Taiwan.
• Chia-Hung Lin
  Department of Electrical Engineering, Kao-Yuan University, Kaohsiung, Taiwan.
• Hsin-Ying Lu
  Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, 5 Fuhsing St., Guishan, Taoyuan, Taiwan, 33382.
• Hsin-Ju Chiang
  Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, 5 Fuhsing St., Guishan, Taoyuan, Taiwan, 33382.
• Ho-Kai Wang
  Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, 5 Fuhsing St., Guishan, Taoyuan, Taiwan, 33382.
• Yu-Ting Huang
  Department of Medical Imaging and Intervention, Imaging Core Laboratory, Institute for Radiological Research, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
• Shu-Hang Ng
  Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Linkou, Chang Gung University, Taoyuan, Taiwan.
• Ji-Hong Hong
  Imaging Core Laboratory, Institute for Radiological Research, Chang Gung Memorial Hospital at Linkou and Chang Gung University, 5 Fuhsing St., Guishan, Taoyuan, Taiwan, 33382.
• Tzu-Chen Yen
  Molecular Imaging Center, Chang Gung Memorial Hospital, Linkou, Taoyuan, Taiwan.
• Chyong-Huey Lai
  Imaging Core Laboratory, Institute for Radiological Research, Chang Gung Memorial Hospital at Linkou and Chang Gung University, 5 Fuhsing St., Guishan, Taoyuan, Taiwan, 33382.
• Gigin Lin
  Department of Medical Imaging and Intervention, Imaging Core Laboratory, Institute for Radiological Research, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.

Keywords

External Resources