Residual Metal Artifact Reduction in CT Images: An Unsupervised Residual and Contrastive Learning Approach for Preserving Metal Structures
We hope that this unsupervised learning model can contribute to good achievements in the MAR field while overcoming the limitations of data construction.
Authors
- Byung Chul Lee (ORCID: https://orcid.org/0000-0002-7702-716X)
- YongSoo Kim
- Hyunseok Seo (ORCID: https://orcid.org/0000-0003-0224-8942)
- Jung‐Woo Lee (ORCID: https://orcid.org/0000-0001-9902-347X)
Institutions
- Seoul National University of Science and Technology (KR)
- Kyung Hee Cyber University (KR)
- Korea University (KR)
- Kyung Hee University (KR)
- Kyung Hee University Dental Hospital (KR)
- Bio-Medical Science (South Korea) (KR)
- Korea Institute of Science and Technology (KR)
- Korea University of Science and Technology (KR)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-10-27
- DOI
- https://doi.org/10.1002/mp.70078
- Citations
- 1
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.67