PlaqueViT: a vision transformer model for fully automatic vessel and plaque segmentation in coronary computed tomography angiography
Question A tool for fully automatic and voxelwise segmentation of coronary plaques in coronary CTA (CCTA) is important for both clinical and research usage of the CCTA examination. Findings Segmentation of coronary artery plaques by PlaqueViT was comparable to an expert reader's performance. Clinical relevance This novel, fully automatic deep learning model for voxelwise segmentation of coronary plaques in CCTA is highly relevant for large population studies such as the Swedish CardioPulmonary BioImage Study.
Authors
- Göran M.L. Bergström (ORCID: https://orcid.org/0000-0003-4289-5722)
- Ola Hjelmgren (ORCID: https://orcid.org/0000-0002-8639-6928)
- Erika Fagman (ORCID: https://orcid.org/0000-0002-0983-0313)
- Jennifer Alvén
- David Hagerman (ORCID: https://orcid.org/0000-0002-5193-3789)
- Mårten Sandstedt (ORCID: https://orcid.org/0000-0002-0973-9499)
- Pieter Kitslaar (ORCID: https://orcid.org/0000-0003-3453-2841)
- Richard Petersen
Institutions
- Linköping University (SE)
- Sahlgrenska University Hospital (SE)
- Centre for Medical Systems Biology (NL)
- Region Västra Götaland (SE)
- Chalmers University of Technology (SE)
- University of Gothenburg (SE)
Publication Details
- Journal
- European Radiology
- Published
- 2025-02-05
- DOI
- https://doi.org/10.1007/s00330-025-11410-w
- Citations
- 2
- Primary Topic
- Cardiac Imaging and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 2.72
Funders
- VINNOVA
- Sahlgrenska Universitetssjukhuset
- Göteborgs Universitet
- Svenska Läkaresällskapet