Active learning using deep Bayesian networks for surgical workflow analysis.

Journal: International journal of computer assisted radiology and surgery
Published Date: Apr 9, 2019

Abstract

PURPOSE: For many applications in the field of computer-assisted surgery, such as providing the position of a tumor, specifying the most probable tool required next by the surgeon or determining the remaining duration of surgery, methods for surgical workflow analysis are a prerequisite. Often machine learning-based approaches serve as basis for analyzing the surgical workflow. In general, machine learning algorithms, such as convolutional neural networks (CNN), require large amounts of labeled data. While data is often available in abundance, many tasks in surgical workflow analysis need annotations by domain experts, making it difficult to obtain a sufficient amount of annotations.

Authors

  • Sebastian Bodenstedt
    Division of Translational Surgical Oncology, National Center for Tumor Diseases (NCT), Partner Site Dresden, Dresden, Germany.
  • Dominik Rivoir
    Department for Translational Surgical Oncology, National Center for Tumor Diseases (NCT), Partner Site Dresden, Dresden, Germany.
  • Alexander Jenke
    Department for Translational Surgical Oncology, National Center for Tumor Diseases (NCT), Partner Site Dresden, Dresden, Germany.
  • Martin Wagner
    Department of Biology, Norwegian University of Science and Technology, 5 Høgskoleringen, 7491 Trondheim, Norway. Electronic address: martin.wagner@ntnu.no.
  • Michael Breucha
    Department of Visceral, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany.
  • Beat Müller-Stich
    Department of General, Visceral and Transplant Surgery, University of Heidelberg, Heidelberg, Germany.
  • Sören Torge Mees
    Department of Visceral, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany.
  • Jürgen Weitz
    Department of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
  • Stefanie Speidel
    Division of Translational Surgical Oncology, National Center for Tumor Diseases (NCT), Partner Site Dresden, Dresden, Germany.

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