A neural network algorithm for detection of GI angiectasia during small-bowel capsule endoscopy.

Journal: Gastrointestinal endoscopy
Published Date: Jan 1, 2019

Abstract

BACKGROUND AND AIMS: GI angiectasia (GIA) is the most common small-bowel (SB) vascular lesion, with an inherent risk of bleeding. SB capsule endoscopy (SB-CE) is the currently accepted diagnostic procedure. The aim of this study was to develop a computer-assisted diagnosis tool for the detection of GIA.

Authors

  • Romain Leenhardt
    Sorbonne University, Department of Hepato-Gastroenterology, APHP, Saint Antoine Hospital, Paris, France.
  • Pauline Vasseur
    ETIS, Université de Cergy-Pontoise, ENSEA, CNRS, Cergy-Pontoise Cedex, France.
  • Cynthia Li
    Sorbonne University, Department of Hepato-Gastroenterology, APHP, Saint Antoine Hospital, Paris, France; Drexel University, College of Arts & Sciences, Philadelphia, Pennsylvania, USA.
  • Jean Christophe Saurin
    Department of Endoscopy and Gastroenterology, Pavillon L, Hôpital Edouard Herriot, Lyon, France.
  • Gabriel Rahmi
    Georges Pompidou European Hospital, APHP, Department of Gastroenterology and Endoscopy, Paris, France.
  • Franck Cholet
    Digestive Endoscopy Unit, University Hospital, Brest, France.
  • Aymeric Becq
    Sorbonne University, Department of Hepato-Gastroenterology, APHP, Saint Antoine Hospital, Paris, France.
  • Philippe Marteau
    Sorbonne University, Department of Hepato-Gastroenterology, APHP, Saint Antoine Hospital, Paris, France.
  • Aymeric Histace
    ETIS, Université de Cergy-Pontoise, ENSEA, CNRS, Cergy-Pontoise Cedex, France.
  • Xavier Dray
    Sorbonne University, Department of Hepato-Gastroenterology, APHP, Saint Antoine Hospital, Paris, France; ETIS, Université de Cergy-Pontoise, ENSEA, CNRS, Cergy-Pontoise Cedex, France.

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