Deep learning algorithms for automated detection of Crohn's disease ulcers by video capsule endoscopy.

Journal: Gastrointestinal endoscopy
PMID:

Abstract

BACKGROUND AND AIMS: The aim of our study was to develop and evaluate a deep learning algorithm for the automated detection of small-bowel ulcers in Crohn's disease (CD) on capsule endoscopy (CE) images of individual patients.

Authors

  • Eyal Klang
    Division of Data-Driven and Digital Medicine (D3M), Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Yiftach Barash
    Department of Diagnostic Imaging, Chaim Sheba Medical Center, Tel Hashomer, Israel.
  • Reuma Yehuda Margalit
    Department of Gastroenterology, Sheba Medical Center, Tel Hashomer, Israel.
  • Shelly Soffer
    From the Department of Diagnostic Imaging, Sheba Medical Center, Emek HaEla St 1, Ramat Gan, Israel (S.S., M.M.A., E.K.); Faculty of Engineering, Department of Biomedical Engineering, Medical Image Processing Laboratory, Tel Aviv University, Tel Aviv, Israel (A.B., H.G.); and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel (S.S., O.S.).
  • Orit Shimon
    From the Department of Diagnostic Imaging, Sheba Medical Center, Emek HaEla St 1, Ramat Gan, Israel (S.S., M.M.A., E.K.); Faculty of Engineering, Department of Biomedical Engineering, Medical Image Processing Laboratory, Tel Aviv University, Tel Aviv, Israel (A.B., H.G.); and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel (S.S., O.S.).
  • Ahmad Albshesh
    Department of Gastroenterology, Sheba Medical Center, Tel Hashomer, Israel.
  • Shomron Ben-Horin
    Department of Gastroenterology, Sheba Medical Center, Tel Hashomer, Israel.
  • Marianne Michal Amitai
    Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Israel.
  • Rami Eliakim
    Department of Gastroenterology, Sheba Medical Center, Tel Hashomer, Israel.
  • Uri Kopylov
    Department of Gastroenterology, Sheba Medical Center, Tel Hashomer, Israel.