Deep Learning–Based Segmentation of Coronary Arteries and Stenosis Detection in X-Ray Coronary Angiography
The models achieved performance levels on par with experts in coronary artery segmentation and detection of significant stenoses in the main arteries.
Authors
- Vincent Auvray
- Daniel Gold (ORCID: https://orcid.org/0009-0007-5092-1157)
- Nikoloz Shekiladze (ORCID: https://orcid.org/0000-0003-0127-5703)
- Alexander Haak
- Jasper L. Selder (ORCID: https://orcid.org/0000-0002-0777-491X)
- Steven A. J. Chamuleau (ORCID: https://orcid.org/0000-0002-9952-6701)
- Berto J. Bouma (ORCID: https://orcid.org/0000-0002-1433-9692)
- Mitchel Molenaar
- Elsa Hebbo (ORCID: https://orcid.org/0000-0002-3378-8821)
- Mark J. Schuuring (ORCID: https://orcid.org/0000-0002-2843-1852)
- Niels Verouden (ORCID: https://orcid.org/0000-0002-8480-0392)
- Pratik B. Sandesara (ORCID: https://orcid.org/0000-0002-2809-8789)
- Yida Zhao (ORCID: https://orcid.org/0009-0009-4569-9103)
- Folkert W Asselbergs
- Javier Oliván Bescós
- Shaimaa M. Sakr
- William J. Nicholson
- Syed Ahmad
- Jelle D. Nieuwendijk
- Martijn S. van Mourik
Institutions
- Philips (Finland) (FI)
- Emory University (US)
- Medisch Spectrum Twente (NL)
- Amsterdam Neuroscience (NL)
- Amsterdam University Medical Centers (NL)
- University College London (GB)
- Amsterdam University of Applied Sciences (NL)
- University of Twente (NL)
Publication Details
- Journal
- JACC Advances
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1016/j.jacadv.2025.102360
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00