Artificial intelligence machine learning-based coronary CT fractional flow reserve (CT-FFR): Impact of iterative and filtered back projection reconstruction techniques.
Journal:
Journal of cardiovascular computed tomography
Published Date:
Oct 26, 2018
Abstract
BACKGROUND: The influence of computed tomography (CT) reconstruction algorithms on the performance of machine-learning-based CT-derived fractional flow reserve (CT-FFR) has not been investigated. CT-FFR values and processing time of two reconstruction algorithms were compared using an on-site workstation.
Authors
Keywords
Aged
Computed Tomography Angiography
Coronary Angiography
Coronary Artery Disease
Coronary Stenosis
Coronary Vessels
Female
Fractional Flow Reserve, Myocardial
Humans
Machine Learning
Male
Middle Aged
Predictive Value of Tests
Radiographic Image Interpretation, Computer-Assisted
Reproducibility of Results
Retrospective Studies
Severity of Illness Index
Workflow