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Improving image quality with super-resolution deep-learning-based reconstruction in coronary CT angiography.

Yasunori NagayamaTakafumi EmotoYuki KatoMasafumi KidohSeitaro OdaDaisuke SakabeYoshinori FunamaTakeshi NakauraHidetaka HayashiSentaro TakadaRyutaro UchimuraMasahiro HatemuraKenichi TsujitaToshinori Hirai
Published in: European radiology (2023)
• SR-DLR designed for CCTA improved image sharpness, noise property, and delineation of cardiac structures with reduced blooming artifacts from calcified plaques relative to HIR, MBIR, and NR-DLR. • In the task-based image-quality assessments, SR-DLR yielded better spatial resolution, noise property, and detectability for objects simulating the coronary lumen, coronary calcifications, and noncalcified plaques than other reconstruction techniques. • The image reconstruction times of SR-DLR were shorter than those of MBIR, potentially serving as a novel standard-of-care reconstruction technique for CCTA performed on a 320-row CT scanner.
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