Clinical validation of enhanced CT imaging for distal radius fractures through conditional Generative Adversarial Networks (cGAN)
In our study utilizing cGAN for enhancing CT imaging resolution, the authors found that the method, which focuses on the difference value between 3 mm and 1 mm images (Method 2), consistently outperformed.
Authors
- Hyojune Kim (ORCID: https://orcid.org/0000-0001-7665-536X)
- Sang-Il Oh (ORCID: https://orcid.org/0000-0002-3972-5119)
- Seung Min Ryu (ORCID: https://orcid.org/0000-0001-6946-1428)
- Kyoung Hwan Koh (ORCID: https://orcid.org/0000-0002-6181-9621)
- Young Ho Shin (ORCID: https://orcid.org/0000-0002-9388-9720)
- Kyungnam Kim (ORCID: https://orcid.org/0000-0002-3131-8586)
- Ji-Soo Keum
- In‐Ho Jeon
Institutions
- Ulsan College (KR)
- Asan Medical Center (KR)
- University of Ulsan (KR)
- Chung-Ang University Hospital (KR)
Publication Details
- Journal
- PLoS ONE
- Published
- 2024-08-16
- DOI
- https://doi.org/10.1371/journal.pone.0308346
- Citations
- 5
- Primary Topic
- Orthopedic Surgery and Rehabilitation
- Type
- article
- Field-Weighted Citation Impact
- 2.86
Funders
- National Research Foundation
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea