Comparative evaluation of supervised and unsupervised deep learning strategies for denoising hyperpolarized <scp> <sup>129</sup> Xe </scp> lung <scp>MRI</scp>
Low SNR may impair the potential of <sup>129</sup>Xe MRI for clinical diagnosis and lung function assessment. The evaluation of supervised and unsupervised DL denoising methods enhanced <sup>129</sup>Xe imaging quality, offering promise for improved clinical interpretation and diagnosis.
Authors
- Laura L. Walkup (ORCID: https://orcid.org/0000-0002-5060-6401)
- Zackary I. Cleveland (ORCID: https://orcid.org/0000-0001-6195-9061)
- Abdullah Bdaiwi (ORCID: https://orcid.org/0000-0001-7835-7032)
- Riaz Hussain (ORCID: https://orcid.org/0000-0003-4406-2345)
- Erik B. Hysinger (ORCID: https://orcid.org/0000-0002-9222-898X)
- Jason C. Woods (ORCID: https://orcid.org/0000-0002-8080-7511)
- Matthew M. Willmering (ORCID: https://orcid.org/0000-0002-4356-9622)
Institutions
- Cincinnati Children's Hospital Medical Center (US)
- University of Cincinnati (US)
Publication Details
- Journal
- Magnetic Resonance in Medicine
- Published
- 2025-08-14
- DOI
- https://doi.org/10.1002/mrm.70033
- Citations
- 2
- Primary Topic
- Optical Polarization and Ellipsometry
- Type
- article
- Field-Weighted Citation Impact
- 1.35