Advancing artificial intelligence applicability in endoscopy through source-agnostic camera signal extraction from endoscopic images.

Journal: PloS one
Published Date: Jun 11, 2025

Abstract

INTRODUCTION: Successful application of artificial intelligence (AI) in endoscopy requires effective image processing. Yet, the plethora of sources for endoscopic images, such as different processor-endoscope combinations or capsule endoscopy devices, results in images that vastly differ in appearance. These differences hinder the generalizability of AI models in endoscopy.

Authors

  • Ioannis Kafetzis
    Interventional and Experimental Endoscopy (InExEn), Internal Medicine II, University Hospital Würzburg, Würzburg, Germany.
  • Philipp Sodmann
    Institute of Bioinformatics, University Medicine Greifswald, Greifswald, Germany. DZHK (German Center for Cardiological Research), partner site Greifswald, Greifswald, Germany.
  • Robert Hüneburg
    Department of Internal Medicine I and National Center for Hereditary Tumor Syndromes, University Hospital Bonn, Bonn, Germany; European Reference Network for Genetic Tumor Risk Syndromes (ERN Genturis), Bonn, Germany.
  • Jacob Nattermann
    Department of Internal Medicine I, University Hospital Bonn, Bonn, Germany.
  • Nora Martens
    Department of Medicine I, University Hospital Dresden, Dresden, Germany.
  • Daniel R Englmann
    Department of Internal Medicine II, Hospital of Worms, Worms, Germany.
  • Wolfram G Zoller
    Department of Internal Medicine and Gastroenterology, Katharinenhospital, Stuttgart, Germany.
  • Alexander Meining
    Department of Gastroenterology, University of Würzburg, Würzburg, Germany.
  • Alexander Hann
    Department of Internal Medicine II, Interventional and Experimental Endoscopy (InExEn), University Hospital Wuerzburg, Würzburg, Germany.

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