Denoising complex‐valued diffusion <scp>MR</scp> images using a two‐step, nonlocal principal component analysis approach
The proposed denoising method has the utility for improving image quality for diffusion MRI with a few diffusion directions and is believed to benefit many applications, especially those aiming to achieve high-quality parametric mapping using only a few image volumes.
Authors
- Ziyi Pan (ORCID: https://orcid.org/0000-0002-7138-238X)
- Kâmil Uǧurbil (ORCID: https://orcid.org/0000-0002-8475-9334)
- Xiaodong Ma (ORCID: https://orcid.org/0000-0001-7158-8073)
- Xiaoping Wu (ORCID: https://orcid.org/0000-0001-6021-9088)
- Hua Guo (ORCID: https://orcid.org/0000-0002-0482-1493)
- Zhe Zhang (ORCID: https://orcid.org/0000-0001-8220-8443)
- Xinyu Ye
Institutions
- University of Minnesota (US)
- Capital Medical University (CN)
- University of Utah (US)
- University of Oxford (GB)
- Beijing Tian Tan Hospital (CN)
- Wellcome Centre for Integrative Neuroimaging (GB)
- Resonance Research (United States) (US)
- Tsinghua University (CN)
Publication Details
- Journal
- Magnetic Resonance in Medicine
- Published
- 2025-03-13
- DOI
- https://doi.org/10.1002/mrm.30502
- Citations
- 4
- Primary Topic
- Advanced Neuroimaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 5.44
Funders
- National Institutes of Health
- National Key Research and Development Program of China