Optimization of deep learning–based denoising for arterial spin labeling: Effects of averaging and training strategies
This study supports the use of DL-based denoising in improving the image quality of ASL and reducing scan time and provides insights to help optimize DL-denoising pipelines.
Authors
- Hossein Rahimzadeh
- Naveed Ilyas (ORCID: https://orcid.org/0000-0002-8220-4474)
- Greg Zaharchuk (ORCID: https://orcid.org/0000-0001-5781-8848)
- Arun Sharma (ORCID: https://orcid.org/0000-0003-2554-8876)
- Jia Guo (ORCID: https://orcid.org/0000-0003-3371-5857)
Institutions
- University of California, Riverside (US)
- Stanford University (US)
Publication Details
- Journal
- Magnetic Resonance in Medicine
- Published
- 2025-08-05
- DOI
- https://doi.org/10.1002/mrm.70013
- Citations
- 1
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- National Institutes of Health