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

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.

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Bibliographic Details
Published inThe Journal of hand surgery, European volume Vol. 49; no. 4; p. 507
Main Authors Teule, E H S, Lessmann, N, van der Heijden, E P A, Hummelink, S
Format Journal Article
LanguageEnglish
Published England 01.04.2024
Subjects
Deep learning
carpal bones
four-dimensional computed tomography
carpal instability
automatic segmentation
artificial intelligence
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Summary: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.
ISSN:2043-6289
DOI:10.1177/17531934231209876