Exploiting the potential of unlabeled endoscopic video data with self-supervised learning.

Journal: International journal of computer assisted radiology and surgery
Published Date: Apr 27, 2018

Abstract

PURPOSE: Surgical data science is a new research field that aims to observe all aspects of the patient treatment process in order to provide the right assistance at the right time. Due to the breakthrough successes of deep learning-based solutions for automatic image annotation, the availability of reference annotations for algorithm training is becoming a major bottleneck in the field. The purpose of this paper was to investigate the concept of self-supervised learning to address this issue.

Authors

  • Tobias Roß
    German Cancer Research Center (DKFZ), Computer Assisted Medical Interventions, Heidelberg, Germany.
  • David Zimmerer
    Medical Image Computing, German Cancer Research Center, Im Neuenheimer Feld 581, 69210, Heidelberg, Germany.
  • Anant Vemuri
    Computer Assisted Medical Interventions, German Cancer Research Center, Im Neuenheimer Feld 581, 69210, Heidelberg, Germany.
  • Fabian Isensee
  • Manuel Wiesenfarth
    Division of Biostatistics, German Cancer Research Center, Im Neuenheimer Feld 581, 69210, Heidelberg, Germany.
  • Sebastian Bodenstedt
    Division of Translational Surgical Oncology, National Center for Tumor Diseases (NCT), Partner Site Dresden, Dresden, Germany.
  • Fabian Both
    understand.ai, Hirschstr. 71, 76133, Karlsruhe, Germany.
  • Philip Kessler
    understand.ai, Hirschstr. 71, 76133, Karlsruhe, Germany.
  • Martin Wagner
    Department of Biology, Norwegian University of Science and Technology, 5 Høgskoleringen, 7491 Trondheim, Norway. Electronic address: martin.wagner@ntnu.no.
  • Beat Müller
    Department of General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.
  • Hannes Kenngott
    Department of General, Abdominal and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany.
  • Stefanie Speidel
    Division of Translational Surgical Oncology, National Center for Tumor Diseases (NCT), Partner Site Dresden, Dresden, Germany.
  • Annette Kopp-Schneider
    Division of Biostatistics, German Cancer Research Center, Im Neuenheimer Feld 581, 69210, Heidelberg, Germany.
  • Klaus Maier-Hein
    Medical Image Analysis, Division Medical Image Computing, DKFZ Heidelberg, Germany.
  • Lena Maier-Hein
    German Cancer Research Center (DKFZ), Computer Assisted Medical Interventions, Heidelberg, Germany.

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