A device‐dependent auto‐segmentation method based on combined generalized and single‐device datasets
The results suggest that combining the generalized dataset with a single scanner dataset resulted in an overall improvement in model performance for that device image.
Authors
- K. Chung (ORCID: https://orcid.org/0000-0002-9843-1495)
- Yousun Ko (ORCID: https://orcid.org/0000-0002-2181-9555)
- Myonggeun Yoon (ORCID: https://orcid.org/0000-0002-4230-9458)
- Hwanhee Park (ORCID: https://orcid.org/0000-0002-3337-408X)
- Yunhui Jo (ORCID: https://orcid.org/0000-0003-2207-5997)
- Yongha Gi
- Haeyoung Kim (ORCID: https://orcid.org/0000-0003-1808-7573)
- Jinyoung Hong (ORCID: https://orcid.org/0000-0001-8855-7900)
- Jong-Hyun Kim (ORCID: https://orcid.org/0000-0003-3943-1644)
- Hyeongjin Lim
- Sung Hwan Ahn
Institutions
- Korea University (KR)
- Samsung Medical Center (KR)
- Sungkyunkwan University (KR)
Publication Details
- Journal
- Medical Physics
- Published
- 2024-12-19
- DOI
- https://doi.org/10.1002/mp.17570
- Citations
- 1
- Primary Topic
- Advanced Neural Network Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.25
Funders
- Korea Medical Device Development Fund
- National Research Foundation
- Ministry of Trade, Industry and Energy
- Korea Institute for Advancement of Technology
- National Research Foundation of Korea