Deep learning for sensitive detection of Helicobacter Pylori in gastric biopsies.

Journal: BMC gastroenterology
Published Date: Dec 11, 2020

Abstract

BACKGROUND: Helicobacter pylori, a 2 × 1 μm spiral-shaped bacterium, is the most common risk factor for gastric cancer worldwide. Clinically, patients presenting with symptoms of gastritis, routinely undergo gastric biopsies. The following histo-morphological evaluation dictates therapeutic decisions, where antibiotics are used for H. pylori eradication. There is a strong rational to accelerate the detection process of H. pylori on histological specimens, using novel technologies, such as deep learning.

Authors

  • Sebastian Klein
    Else-Kröner-Forschungskolleg, Clonal Evolution in Cancer, University Hospital Cologne, Cologne, Germany. Sebastian.Klein@uk-koeln.de.
  • Jacob Gildenblat
    DeePathology.ai, Raanana, Israel.
  • Michaele Angelika Ihle
    Institute for Pathology, University Hospital Cologne, Cologne, Germany.
  • Sabine Merkelbach-Bruse
    Institute for Pathology, University Hospital Cologne, Cologne, Germany.
  • Ka-Won Noh
    Institute for Pathology, University Hospital Cologne, Cologne, Germany.
  • Martin Peifer
    Department of Translational Genomics, Center of Integrated Oncology Cologne-Bonn, Medical Faculty, University of Cologne, 50931, Cologne, Germany.
  • Alexander Quaas
    Institute of Pathology, University Hospital Cologne, Cologne, Germany.
  • Reinhard Büttner
    Institute of Pathology, University Hospital Cologne, Cologne, Germany.

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