Improving pose accuracy and geometry in neural radiance field‐based medical image synthesis
The proposed approach addresses the pose reconstruction challenge in MedNeRF, enhances the anatomical detail, and reduces noise in generated images. The use of HTDataset and the innovative discriminator structure lead to significant improvements in the accuracy and quality of the rendered images, setting a new benchmark in the field.
Authors
- Wenguang W. Hou (ORCID: https://orcid.org/0000-0002-0986-6906)
- Jingxian Dong
- Mingyue Ding (ORCID: https://orcid.org/0000-0001-8769-4153)
- 朱洪玲 Zhu Hongling
- Twaha B. Kabika (ORCID: https://orcid.org/0009-0008-8571-9407)
- Xiaoyu Wang (ORCID: https://orcid.org/0000-0002-6800-1275)
- Siyuan Zhang (ORCID: https://orcid.org/0000-0002-0084-2609)
- Xianbo Deng
- Cai Hongsen
Institutions
- Union Hospital (HK)
- Tongji Hospital (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-04-14
- DOI
- https://doi.org/10.1002/mp.17832
- Citations
- 1
- Primary Topic
- Computer Graphics and Visualization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 3.54
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China