Deep learning-based recognition of key anatomical structures during robot-assisted minimally invasive esophagectomy.

Journal: Surgical endoscopy
Published Date:

Abstract

OBJECTIVE: To develop a deep learning algorithm for anatomy recognition in thoracoscopic video frames from robot-assisted minimally invasive esophagectomy (RAMIE) procedures using deep learning.

Authors

  • R B den Boer
    Department of Surgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.
  • T J M Jaspers
    Department of Biomedical Engineering, Eindhoven University of Technology, Groene Loper 3, 5612 AE, Eindhoven, The Netherlands.
  • C de Jongh
    Department of Surgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.
  • J P W Pluim
    Medical Image Analysis Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
  • F van der Sommen
    Department of Electrical Engineering, Eindhoven University of Technology, Groene Loper 19, 5612 AP, Eindhoven, The Netherlands.
  • T Boers
    Department of Electrical Engineering, Eindhoven University of Technology, Groene Loper 19, 5612 AP, Eindhoven, The Netherlands.
  • R van Hillegersberg
    Department of Surgery, University Medical Center Utrecht, Utrecht, The Netherlands. r.vanhillegersberg@umcutrecht.nl.
  • M A J M Van Eijnatten
    Department of Biomedical Engineering, Eindhoven University of Technology, Groene Loper 3, 5612 AE, Eindhoven, The Netherlands.
  • J P Ruurda
    Department of Surgery, University Medical Center Utrecht, Utrecht, The Netherlands.