Leveraging Clinical Text and Class Conditioning for 3D Prostate MRI Generation
The proposed CCELLA-centric pipeline enables radiology report and class-conditioned LDM training for high-quality medical image synthesis given limited data volume and human data annotation, improving LDM performance and scientific accessibility.
Authors
- Babak Taati (ORCID: https://orcid.org/0000-0001-9763-4293)
- Emerson Paul Grabke
- Masoom A. Haider (ORCID: https://orcid.org/0000-0002-7165-8315)
Publication Details
- Journal
- IEEE Transactions on Biomedical Engineering
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tbme.2025.3648426
- Primary Topic
- Generative Adversarial Networks and Image Synthesis
- Type
- article
- Field-Weighted Citation Impact
- 0.00