Automatic segmentation and labelling of wrist bones in four-dimensional computed tomography datasets via deep learning.
| Title: | Automatic segmentation and labelling of wrist bones in four-dimensional computed tomography datasets via deep learning. |
|---|---|
| Authors: | Teule, E.H.S.; Lessmann, N.; Heijden, E.P.A. van der; Hummelink, S. |
| Source: | Journal of Hand Surgery. European Volume, 49, 4, pp. 507-509 |
| Publication Year: | 2024 |
| Collection: | Radboud University: DSpace |
| Subject Terms: | Orthopaedics - Radboud University Medical Center; Plastic Surgery - Radboud University Medical Center |
| Description: | Contains fulltext : 304547.pdf (Publisher’s version ) (Open Access) ; 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. ; 01 april 2024 |
| Document Type: | article in journal/newspaper |
| Language: | unknown |
| Relation: | https://repository.ubn.ru.nl//bitstream/handle/2066/304547/304547.pdf; https://hdl.handle.net/2066/304547 |
| DOI: | 10.1177/17531934231209876 |
| Availability: | https://hdl.handle.net/2066/304547; https://repository.ubn.ru.nl//bitstream/handle/2066/304547/304547.pdf; https://doi.org/10.1177/17531934231209876 |
| Accession Number: | edsbas.103ED57C |
| Database: | BASE |