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Fig. 5 | Journal of Cardiovascular Imaging

Fig. 5

From: Super-resolution deep learning image reconstruction: image quality and myocardial homogeneity in coronary computed tomography angiography

Fig. 5

A 63-year-old man with coronary artery calcification and myocardial bridging underwent coronary computed tomography (CT) angiography. The coronary CT angiography images reconstructed using for different methods: filtered-back projection (FBP), hybrid iterative reconstruction (IR), deep learning image reconstruction (DLR), and super-resolution (SR) DLR. Axial images are shown for each reconstruction. SR-DLR demonstrates better delineation of calcification (red arrows) with lower blooming artifacts, sharper branch visualization, and the least image noise compared with other image reconstructions. SR-DLR enhances the delineation of the boundary between the distal segment of the coronary artery (white arrows) and adjacent structure, and it provides better visualization of deep myocardial bridging in the mid left anterior descending artery (LAD; green arrows). Red boxes indicate the magnified image of the proximal segment of the LAD, while blue boxes indicate the magnified image of the distal segment of the LAD

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