A Deep Learning Model to Detect Acute MCA Occlusion on High-Resolution Noncontrast Head CT
A DL model can detect acute MCA occlusion from high-resolution NCCT with accuracy approaching that of CTA. By means of this tool, most candidate thrombectomy patients may be identified with NCCT alone, possibly aiding stroke triage in settings that lack CTA or are otherwise resource-constrained.
Authors
- Peter Chang (ORCID: https://orcid.org/0000-0001-7645-7865)
- David Fussell (ORCID: https://orcid.org/0009-0003-0833-9148)
- Juan Guillermo Velásquez López
Institutions
- University of California, Irvine (US)
Publication Details
- Journal
- American Journal of Neuroradiology
- Published
- 2025-08-08
- DOI
- https://doi.org/10.3174/ajnr.a8954
- Primary Topic
- Acute Ischemic Stroke Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00