Automation of Wilms' tumor segmentation by artificial intelligence.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society
PMID: 38956718

Abstract

BACKGROUND: 3D reconstruction of Wilms' tumor provides several advantages but are not systematically performed because manual segmentation is extremely time-consuming. The objective of our study was to develop an artificial intelligence tool to automate the segmentation of tumors and kidneys in children.

Authors

  • Olivier Hild
    Department of Pediatric Surgery, CHU Besançon, 3 boulevard Fleming, Besançon, F-25000, France.
  • Pierre Berriet
    Université de Franche-Comté, FEMTO-ST Institute, DISC, Besançon, F-25000, France.
  • Jérémie Nallet
    Department of Pediatric Surgery, CHU Besançon, 3 boulevard Fleming, Besançon, F-25000, France.
  • Lorédane Salvi
    Department of Pediatric Surgery, CHU Besançon, 3 boulevard Fleming, Besançon, F-25000, France.
  • Marion Lenoir
    Department of Radiology, CHU Besançon, Besançon, F-25000, France.
  • Julien Henriet
    FEMTO-ST Institute, DISC, CNRS, Univ. Bourgogne-Franche-Comté, 16 route de Gray, Besançon 25030, France. Electronic address: julien.henriet@univ-fcomte.fr.
  • Jean-Philippe Thiran
    Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland.
  • Frédéric Auber
    Department of Pediatric Surgery, CHU Besançon, 3 boulevard Fleming, Besançon, F-25000, France.
  • Yann Chaussy
    Centre Hospitalier Régional Universitaire Jean Minjoz, 3 Boulevard Fleming, 25030, Besançon, France. Electronic address: ychaussy@chu-besancon.fr.

Keywords

External Resources

Popular Topics
Recent Journals