Quantitative image quality metrics enable resource-efficient quality control of clinically applied AI-based reconstructions in MRI
IQMs are effective for QC of AI-based MR reconstructions, offering resource-efficient alternatives to repeated radiologist evaluations. Future work should expand this to other imaging applications and assess additional measures.
Authors
- Jessica Winfield (ORCID: https://orcid.org/0000-0001-6069-5252)
- Olivier White (ORCID: https://orcid.org/0000-0002-1411-6667)
- Brandon Whitcher (ORCID: https://orcid.org/0000-0002-6452-2399)
- Spencer A. Thomas (ORCID: https://orcid.org/0000-0002-9260-1561)
- M Cashmore (ORCID: https://orcid.org/0000-0003-0098-0742)
- Matt G. Hall (ORCID: https://orcid.org/0000-0002-9530-5477)
- Dow‐Mu Koh (ORCID: https://orcid.org/0000-0001-7654-8011)
- Joshua Shur (ORCID: https://orcid.org/0000-0002-4569-4785)
- David J. Collins (ORCID: https://orcid.org/0000-0001-8281-1496)
- Georgina Hopkinson (ORCID: https://orcid.org/0000-0003-4967-8886)
- Geoff Charles‐Edwards (ORCID: https://orcid.org/0000-0002-8369-4604)
- Francesca Castagnoli (ORCID: https://orcid.org/0000-0003-2407-7451)
- Andrew Thompson
- C. H. Harrison
Institutions
- Royal Marsden NHS Foundation Trust (GB)
- National Physical Laboratory (GB)
- Institute of Cancer Research (GB)
- Cancer Research UK (GB)
Publication Details
- Journal
- Magnetic Resonance Materials in Physics Biology and Medicine
- Published
- 2025-05-24
- DOI
- https://doi.org/10.1007/s10334-025-01253-3
- Citations
- 1
- Primary Topic
- Radiation Dose and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- Royal Marsden NHS Foundation Trust
- Government of the United Kingdom
- NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research
- Cancer Research UK
- National Institute for Health and Care Research
- Department of Health and Social Care
- National Physical Laboratory