Denoising 7T Structural MRI with Conditional Generative Diffusion Models
Motivation: 7T MRI offers ultra-high resolution, but the commonly used long acquisitions are challenging, especially for elderly subjects. Goal(s): Efficiently denoising 7T MRI images from a short acquisition without sacrificing image quality. Approach: We introduced the 7T Conditional Diffusion Model (7TCDM), a conditional diffusion model derived from generative AI that is trained on raw acquisitions and references high-quality low-noise images to guide the denoising process and reconstruct high-quality images. Results: 7TCDM significantly reduced noise and artifacts, improving image quality over each acquisition and outperforming the Convolutional Neural Network (CNN)-based model in maintaining image details. Impact: Our newly introduced 7T Conditional Diffusion Model (7TCDM) enables faster MRI acquisition by providing high-quality denoised images from shorter scans, increasing the feasibility of scanning patients in shorter times while preserving essential anatomical details.
Authors
- Michael Zeineh (ORCID: https://orcid.org/0000-0002-6940-9096)
- Marios Georgiadis (ORCID: https://orcid.org/0000-0003-0733-4559)
- Brian K. Rutt (ORCID: https://orcid.org/0000-0001-6516-0505)
- Julian Maclaren (ORCID: https://orcid.org/0000-0001-7073-2926)
- Yixin Wang (ORCID: https://orcid.org/0000-0003-0364-0823)
- Yihao Liang
- Mackenzie Carlson (ORCID: https://orcid.org/0000-0002-0857-3116)
- Phillip DiGiacomo (ORCID: https://orcid.org/0000-0002-2441-4086)
- Greg Zaharchuk (ORCID: https://orcid.org/0000-0001-5781-8848)
- Binxu Li
- Hossein Moein Taghavi (ORCID: https://orcid.org/0000-0002-8585-1634)
- Elizabeth C. Mormino (ORCID: https://orcid.org/0000-0002-4542-6537)
- Victor W. Henderson (ORCID: https://orcid.org/0000-0003-1198-9240)
- Mark R. Bell (ORCID: https://orcid.org/0000-0002-7409-4877)
- Wei Shao (ORCID: https://orcid.org/0000-0002-8554-7245)
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2025-09-16
- DOI
- https://doi.org/10.58530/2025/3840
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00