Deep learning for liver lesion segmentation and classification on staging CT scans of colorectal cancer patients: a multi-site technical validation study.

Abstract

Authors

• U Bashir
  Radiology Department, St Barts Hospital, W Smithfield, London EC1A 7BE, UK. Electronic address: drusmanbashir@gmail.com.
• C Wang
  Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.
• R Smillie
  Radiology Department, St Barts Hospital, W Smithfield, London EC1A 7BE, UK. Electronic address: robert.smillie2@nhs.net.
• A K Rayabat Khan
  School of Electronic Engineering and Computer Science, Queen Mary University of London, UK; Digital Environment Research Institute, Queen Mary University of London, London E1 1HH, UK. Electronic address: acw676@qmul.ac.uk.
• H Tamer Ahmed
  School of Electronic Engineering and Computer Science, Queen Mary University of London, UK. Electronic address: h.t.ahmed@qmul.ac.uk.
• K Ordidge
  Radiology Department, St Barts Hospital, W Smithfield, London EC1A 7BE, UK. Electronic address: katherine.ordidge@nhs.net.
• N Power
  Radiology Department, St Barts Hospital, W Smithfield, London EC1A 7BE, UK. Electronic address: niall.power1@nhs.net.
• M Gerlinger
  Barts Cancer Institute, Queen Mary University, London EC1M 6BQ, UK. Electronic address: marco.gerlinger@nhs.net.
• G Slabaugh
  Digital Environment Research Institute, Queen Mary University of London, London E1 1HH, UK. Electronic address: g.slabaugh@qmul.ac.uk.
• Q Zhang
  Department of Radiology, People's Hospital of Qinghai Province, Xining 810000, China.

Keywords

External Resources