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Current Cardiology Reports|July 11, 2020
Machine Learning and Coronary Artery Calcium ScoringHeon Lee, Simon Martin, Jeremy R Burt, et al.
European Heart Journal. Cardiovascular Imaging|July 29, 2021
Deep learning for vessel-specific coronary artery calcium scoring: validation on a multi-centre datasetDavid J Winkel, V Reddappagari Suryanarayana, A Mohamed Ali, et al.
Medical Physics|December 11, 2013
CONRAD--a software framework for cone-beam imaging in radiologyAndreas Maier, Hannes G Hofmann, Martin Berger, et al.
European Radiology|July 4, 2020
A fully automated software platform for structural mitral valve analysisRobert Steinbach, U Joseph Schoepf, L Parkwood Griffith, et al.
Investigative Radiology|August 22, 2025
Deep Learning-based Automated Coronary Plaque Quantification: First Demonstration With Ultra-high Resolution Photon-counting Detector CT at Different Temporal ResolutionsKonstantin Klambauer, Silvan Daniel Burger, Tristan Thorben Demmert, et al.
Journal of Cardiovascular Computed Tomography|August 23, 2023
AI-based, automated chamber volumetry from gated, non-contrast CTAthira J Jacob, Ola Abdelkarim, Salma Zook, et al.
Radiology|August 20, 2024
CT Myocardial Perfusion and CT-FFR versus Invasive FFR for Hemodynamic Relevance of Coronary Artery DiseaseMartin Soschynski, Roberto Storelli, Clara Birkemeyer, et al.
JACC. Cardiovascular Imaging|October 17, 2021
Prognostic Value of Computed Tomography-Derived Fractional Flow Reserve Comparison With Myocardial Perfusion ImagingAhmed Ibrahim Ahmed, Yushui Han, Mahmoud Al Rifai, et al.
Scientific Reports|August 16, 2022
Sex differences in machine learning computed tomography-derived fractional flow reserveMahmoud Al Rifai, Ahmed Ibrahim Ahmed, Yushui Han, et al.
Circulation. Cardiovascular Imaging|June 20, 2018
Diagnostic Accuracy of a Machine-Learning Approach to Coronary Computed Tomographic Angiography-Based Fractional Flow Reserve: Result From the MACHINE ConsortiumAdriaan Coenen, Young-Hak Kim, Mariusz Kruk, et al.
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