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Fig. 5 | Journal of Cardiovascular Magnetic Resonance

Fig. 5

From: An inline deep learning based free-breathing ECG-free cine for exercise cardiovascular magnetic resonance

Fig. 5

Subjective evaluation of image quality. Three readers evaluated artifacts across all cine scans. Images were classified as having a 1-non-diagnostic, 2-severe, 3-moderate, and 4-minimal artifact level. The mean score of breath-hold ECG-gated segmented cine images was 3.0. The mean score of free-breathing ECG-free real-time cine images reconstructed with GRASP was 3.7 at rest, with 9.1% of images graded as severe. The mean score during post-exercise stress was 3.5, and the percentage of images graded as severe increased to 17.9%. Real-time cine images at rest reconstructed with DRAPR had a mean score of 3.3, with 10.6% of images graded as severe. During post-exercise stress, images had a mean score of 3.1. The percentage of images graded as severe increased to 15.4%. None of the real-time radial cine images reconstructed with GRASP or DRAPR were labeled as non-diagnostic. *p < 0.01. GRASP: golden-angle radial sparse parallel; DRAPR: deep-learning radial acceleration with parallel reconstruction

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