Automatic segmentation and labelling of wrist bones in four-dimensional computed tomography datasets via deep learning.
| Autor: | Teule EHS; Technical Medicine, University of Twente, Enschede, The Netherlands.; Department of Plastic, Reconstructive, and Hand Surgery, Radboud University Medical Center, Nijmegen, The Netherlands., Lessmann N; Department of Radiology, Radboud University Medical Center, Nijmegen, The Netherlands., van der Heijden EPA; Department of Plastic, Reconstructive, and Hand Surgery, Radboud University Medical Center, Nijmegen, The Netherlands.; Department of Plastic, Reconstructive, and Hand Surgery, Jeroen Bosch Hospital, 's-Hertogenbosch, The Netherlands., Hummelink S; Department of Plastic, Reconstructive, and Hand Surgery, Radboud University Medical Center, Nijmegen, The Netherlands. |
|---|---|
| Jazyk: | angličtina |
| Zdroj: | The Journal of hand surgery, European volume [J Hand Surg Eur Vol] 2024 Apr; Vol. 49 (4), pp. 507-509. Date of Electronic Publication: 2023 Oct 26. |
| DOI: | 10.1177/17531934231209876 |
| Abstrakt: | 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. Competing Interests: Declaration of conflicting interestsThe authors have no potential conflicting interests with research, authorship, and/or publication of this article. |
| Databáze: | MEDLINE |
| Externí odkaz: |
|