Utilization of artificial intelligence in minimally invasive right adrenalectomy: recognition of anatomical landmarks with deep learning.

Journal: Acta chirurgica Belgica
PMID: 38841838

Abstract

BACKGROUND: The primary surgical approach for removing adrenal masses is minimally invasive adrenalectomy. Recognition of anatomical landmarks during surgery is critical for minimizing complications. Artificial intelligence-based tools can be utilized to create real-time navigation systems during laparoscopic and robotic right adrenalectomy. In this study, we aimed to develop deep learning models that can identify critical anatomical structures during minimally invasive right adrenalectomy.

Authors

  • Berke Sengun
    Department of General Surgery, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkey.
  • Yalin Iscan
    Department of General Surgery, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkey.
  • Ziya Ata Yazici
    Faculty of Computer and Informatics Engineering, Istanbul Technical University, Istanbul, Turkey.
  • Ismail Cem Sormaz
    Department of General Surgery, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkey.
  • Nihat Aksakal
    Department of General Surgery, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkey.
  • Fatih Tunca
    Department of General Surgery, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkey.
  • Hazim Kemal Ekenel
    Faculty of Computer and Informatics Engineering, Istanbul Technical University, Istanbul, Turkey.
  • Yasemin Giles Senyurek
    Department of General Surgery, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkey.

Keywords

External Resources

Popular Topics
Recent Journals