Self‐supervised denoising diffusion probabilistic models for abdominal DW‐MRI
The ssDDPM effectively reduces motion related deblurring and enhances the quality of DW-MRI images by directly denoising single-repetition (NEX = 1) images while respecting signal decay model constraints. This method improves the assessment of pediatric liver lesions, offering a more accurate and efficient diagnostic tool with reduced scan times, when compared with current clinical practice and other denoising techniques.
Authors
- Serge Vasylechko (ORCID: https://orcid.org/0000-0002-5691-0607)
- Andy Tsai (ORCID: https://orcid.org/0000-0002-0089-6463)
- Onur Afacan (ORCID: https://orcid.org/0000-0003-2112-3205)
- Sila Kurugol (ORCID: https://orcid.org/0000-0002-5081-4569)
Institutions
- Boston Children's Hospital (US)
- Harvard University (US)
Publication Details
- Journal
- Magnetic Resonance in Medicine
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1002/mrm.30536
- Primary Topic
- Advanced Neuroimaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- United States-Israel Binational Science Foundation
- National Institute of Diabetes and Digestive and Kidney Diseases
- National Institute of Neurological Disorders and Stroke
- National Institute of Biomedical Imaging and Bioengineering