Evaluation of AI-based nerve segmentation on ultrasound: relevance of standard metrics in the clinical setting.

Journal: British journal of anaesthesia
PMID:

Abstract

BACKGROUND: In artificial intelligence for ultrasound-guided regional anaesthesia, accurate nerve identification is essential. The technology community typically favours objective metrics of pixel overlap on still-frame images, whereas clinical assessments often use subjective evaluation of cine loops by physician experts. No clinically acceptable threshold of pixel overlap has been defined for nerve segmentation. We investigated the relationship between these approaches and identify thresholds for objective pixel-based metrics when clinical evaluations identify high-quality nerve segmentation.

Authors

  • Bernard V Delvaux
    Department of Anesthesiology and Perioperative Medicine, Ramsay Santé, Claude Galien Private Hospital, Quincy-Sous-Sénart, France.
  • Olivier Maupain
    Department of Anesthesiology and Perioperative Medicine, Ramsay Santé, Claude Galien Private Hospital, Quincy-Sous-Sénart, France.
  • Thomas Giral
    Department of Anesthesiology and Perioperative Medicine, Ramsay Santé, Claude Galien Private Hospital, Quincy-Sous-Sénart, France.
  • James S Bowness
    Nuffield Department of Clinical Anaesthesia, University of Oxford, Oxford, UK; Department of Anaesthesia, Aneurin Bevan University Health Board, Newport, UK. Electronic address: james.bowness@jesus.ox.ac.uk.
  • Luc Mercadal
    Department of Anesthesiology and Perioperative Medicine, Ramsay Santé, Claude Galien Private Hospital, Quincy-Sous-Sénart, France.