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Updated: Jun 23, 2026
Ultrasound Based Assessment of Coronary Artery Flow and Coronary Flow Reserve Using the Pressure Overload Model in Mice
Published on: April 13, 2015
Automating fractional flow reserve (FFR) calculation from CT scans: A rapid workflow using unsupervised learning and
Neeraj Kavan Chakshu1, Jason M Carson1, Igor Sazonov1
1Biomedical Engineering Group, Zienkiewicz Centre for Computational Engineering, Faculty of Science and Engineering, Swansea University, Swansea, UK.
Abstract:
Fractional flow reserve (FFR) provides the functional relevance of coronary atheroma. The FFR-guided strategy has been shown to reduce unnecessary stenting, improve overall health outcome, and to be cost-saving. The non-invasive, coronary computerised tomography (CT) angiography-derived FFR (cFFR) is an emerging method in reducing invasive catheter based measurements. This computational fluid dynamics-based method is laborious as it requires expertise in multidisciplinary analysis of combining image analysis and computational mechanics. In this work, we present a rapid method, powered by unsupervised learning, to automatically calculate cFFR from CT scans without manual intervention.
