Marcel J. W. Greuter
Papers
4
Total Citations
55
H-Index
3
About
Marcel J. W. Greuter is a leading figure in cardiovascular imaging, whose research centers on improving the accuracy of coronary computed tomography (CT) angiography and calcium scoring. His major contributions lie in understanding and correcting for motion artifacts—a critical challenge in cardiac imaging. In a foundational 2009 phantom study (27 citations), he developed a quantitative model to correct coronary calcium scores for the influences of linear motion, calcification density, and temporal resolution across different CT modalities. More recently, Greuter has pioneered the use of deep learning to address these issues, as demonstrated in his 2019 work on motion-corrected coronary calcium scores using convolutional neural networks (22 citations). His 2021 study further classified motion-contaminated plaques to identify key influential factors (4 citations). In a notable 2025 achievement, he showed that motion-compensated virtual monoenergetic imaging on spectral dual-layer CT can reduce contrast dose by 50%—a significant step toward safer, more efficient scans. Greuter’s work, blending rigorous phantom experiments with cutting-edge AI, directly enhances the reliability of non-invasive coronary artery disease assessment.
Research Focus
Key Achievements
Top Papers
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