Accuracy of segment anything model for classification of vascular stenosis in digital subtraction angiography
Dr-SAM proved to be an accurate and efficient tool for vascular assessment, with the potential to streamline diagnostic workflows and reduce variability in stenosis grading. Its ability to deliver rapid and consistent evaluations may contribute to earlier detection of disease and the optimization of treatment strategies. Further studies are needed to confirm these findings in prospective settings and to enhance its capabilities, particularly in the detection of occlusions.
Authors
- Jan Borggrefe (ORCID: https://orcid.org/0000-0003-2908-7560)
- Maria Katz (ORCID: https://orcid.org/0009-0005-2063-1269)
- Iram Shahzadi (ORCID: https://orcid.org/0000-0003-4026-6586)
- Lukas Goertz
- Jan Robert Kröger (ORCID: https://orcid.org/0000-0003-1218-7610)
- Vazgen Zohranyan
- Vagner Navasardyan
- Hayk Navasardyan
Institutions
- Synopsys (Switzerland) (CH)
- St. Theresa's Medical University of Yerevan (AM)
- University Hospital Cologne (DE)
- Johannes Wesling Klinikum Minden (DE)
- Ruhr University Bochum (DE)
Publication Details
- Journal
- CVIR Endovascular
- Published
- 2025-05-19
- DOI
- https://doi.org/10.1186/s42155-025-00560-z
- Primary Topic
- Cerebrovascular and Carotid Artery Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ruhr-Universität Bochum