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Coronary computed tomography angiography (CCTA) is a powerful tool to rule out coronary artery disease (CAD). In the last decade, myocardial perfusion CT (CTP) technique has been developed for the evaluation of myocardial ischemia, thereby increasing positive predictive value for diagnosis of obstructive CAD. A diagnostic strategy combining CCTA and perfusion acquisitions provides both anatomical coronary evaluation and functional evaluation of the stenosis, increasing the specificity and the positive predictive value of cardiac CT.

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Objectives: To develop and validate deep learning (DL)-models that denoise late iodine enhancement (LIE) images and enable accurate extracellular volume (ECV) quantification.

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