Deep transfer learning methods for colon cancer classification in confocal laser microscopy images.

Journal: International journal of computer assisted radiology and surgery
Published Date: Nov 1, 2019

Abstract

PURPOSE: The gold standard for colorectal cancer metastases detection in the peritoneum is histological evaluation of a removed tissue sample. For feedback during interventions, real-time in vivo imaging with confocal laser microscopy has been proposed for differentiation of benign and malignant tissue by manual expert evaluation. Automatic image classification could improve the surgical workflow further by providing immediate feedback.

Authors

  • Nils Gessert
    Hamburg University of Technology, Schwarzenbergstraße 95 21073, Hamburg. Electronic address: mfbeg@sfu.ca.
  • Marcel Bengs
    Institute of Medical Technology, Hamburg University of Technology, Hamburg, Germany.
  • Lukas Wittig
    Department of Pulmology, University Medical Centre Schleswig-Holstein, Lübeck, Germany.
  • Daniel Drömann
    Department of Pulmology, University Medical Centre Schleswig-Holstein, Lübeck, Germany.
  • Tobias Keck
    Department of Surgery, University Medical Centre Schleswig-Holstein, Lübeck, Germany.
  • Alexander Schlaefer
    Institute of Medical Technology, Hamburg University of Technology, Hamburg, Germany. schlaefer@tuhh.de.
  • David B Ellebrecht
    Department of Surgery, University Medical Centre Schleswig-Holstein, Lübeck, Germany.

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