Quantitative Susceptibility Mapping <scp>MRI</scp> With Computer Vision Metrics to Reduce Scan Time for Brain Hemorrhage Assessment
The findings support using shorter QSM MRI protocols for ICH evaluation and suggest CVMs may aid optimization efforts for other clinical imaging protocols.
Authors
- Aristotelis Filippidis (ORCID: https://orcid.org/0000-0002-1568-7613)
- Ajith J. Thomas (ORCID: https://orcid.org/0000-0003-4412-3152)
- Bülent Aslan (ORCID: https://orcid.org/0000-0002-8565-2141)
- Magdy Selim (ORCID: https://orcid.org/0000-0002-1936-3173)
- Huiyu Huang (ORCID: https://orcid.org/0000-0002-8627-6416)
- Yan Wen (ORCID: https://orcid.org/0000-0003-3355-9655)
- Salil Soman (ORCID: https://orcid.org/0000-0002-5887-0717)
- S. Balaji
- Pascal Spincemaille
- Yi Wang (ORCID: https://orcid.org/0009-0008-1484-1325)
Institutions
- Lincoln Medical Center (US)
- Northeastern University (US)
- Beth Israel Deaconess Medical Center (US)
- Barrow Neurological Institute (US)
- Harvard University (US)
- Cornell University (US)
- Cooper Medical School of Rowan University (US)
- Cooper University Health Care (US)
- Weill Cornell Medicine (US)
Publication Details
- Journal
- International Journal of Imaging Systems and Technology
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1002/ima.70070
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- National Institute on Aging
- National Institute of Neurological Disorders and Stroke