Computer-aided classification of colorectal segments during colonoscopy: a deep learning approach based on images of a magnetic endoscopic positioning device.

Journal: Scandinavian journal of gastroenterology
PMID: 36458659

Abstract

OBJECTIVE: Assessment of the anatomical colorectal segment of polyps during colonoscopy is important for treatment and follow-up strategies, but is largely operator dependent. This feasibility study aimed to assess whether, using images of a magnetic endoscope imaging (MEI) positioning device, a deep learning approach can be useful to objectively divide the colorectum into anatomical segments.

Authors

  • Britt B S L Houwen
    Department of Gastroenterology and Hepatology, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam University Medical Centres, location Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands.
  • Fons Hartendorp
    Department of Computer Science, University of Amsterdam, Amsterdam, the Netherlands.
  • Ioanis Giotis
    ZiuZ Visual Intelligence, Gorredijk, the Netherlands.
  • Yark Hazewinkel
    Department of Gastroenterology and Hepatology, Radboud University Nijmegen Medical Center, Radboud University of Nijmegen, Nijmegen, the Netherlands.
  • Paul Fockens
    Department of Gastroenterology and Hepatology, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam University Medical Centres, location Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands.
  • Taco R Walstra
    Department of Computer Science, University of Amsterdam, Amsterdam, the Netherlands.
  • Evelien Dekker
    Department of Gastroenterology and Hepatology, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam University Medical Centres, location Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands.

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