Automatic segmentation and labelling of wrist bones in four-dimensional computed tomography datasets via deep learning

E H S Teule; N Lessmann; E P A van der Heijden; S Hummelink

doi:10.1177/17531934231209876

Automatic segmentation and labelling of wrist bones in four-dimensional computed tomography datasets via deep learning

J Hand Surg Eur Vol. 2024 Apr;49(4):507-509. doi: 10.1177/17531934231209876. Epub 2023 Oct 26.

Authors

E H S Teule^{1

2}, N Lessmann³, E P A van der Heijden^{2

4}, S Hummelink²

Affiliations

¹ Technical Medicine, University of Twente, Enschede, The Netherlands.
² Department of Plastic, Reconstructive, and Hand Surgery, Radboud University Medical Center, Nijmegen, The Netherlands.
³ Department of Radiology, Radboud University Medical Center, Nijmegen, The Netherlands.
⁴ Department of Plastic, Reconstructive, and Hand Surgery, Jeroen Bosch Hospital, 's-Hertogenbosch, The Netherlands.

PMID: 37882645
DOI: 10.1177/17531934231209876

Abstract

This study developed a deep learning model for fully automatic segmentation and labelling of wrist bones from four-dimensional computed tomography (4DCT) scans. This is a crucial step towards implementing 4DCT for diagnosing wrist ligament lesions, reducing time-consuming analysis of extensive data.

Keywords: Deep learning; artificial intelligence; automatic segmentation; carpal bones; carpal instability; four-dimensional computed tomography.

Publication types

Letter

MeSH terms

Carpal Bones*
Deep Learning*
Four-Dimensional Computed Tomography / methods
Humans
Image Processing, Computer-Assisted / methods
Ligaments, Articular
Wrist