Diffusion probabilistic generative models for accelerated, in‐NICU permanent magnet neonatal MRI
Diffusion probabilistic generative models applied with the proposed pipeline to handle challenging real-world datasets could reduce the scan time of in-NICU neonatal MRI.
Authors
- Jonathan I. Tamir (ORCID: https://orcid.org/0000-0001-9113-9566)
- Yamin Arefeen (ORCID: https://orcid.org/0000-0003-2194-1945)
- Bhairav Patel
- Brett Levac (ORCID: https://orcid.org/0000-0002-1182-3438)
- Chang Yueh Ho (ORCID: https://orcid.org/0000-0002-2358-1851)
Institutions
- The University of Texas MD Anderson Cancer Center (US)
- The University of Texas at Austin (US)
Publication Details
- Journal
- Magnetic Resonance in Medicine
- Published
- 2025-06-17
- DOI
- https://doi.org/10.1002/mrm.30585
- Primary Topic
- Fetal and Pediatric Neurological Disorders
- Type
- article
- Field-Weighted Citation Impact
- 0.00