Fig. 7From: An inline deep learning based free-breathing ECG-free cine for exercise cardiovascular magnetic resonanceRepresentative real-time cine images of subjects at post-exercise stress. The NUFFT was used to grid and reconstruct radial k-space data. Artifacts were subsequently suppressed using the GRASP and DRAPR techniques. Images were classified as having a 1-non-diagnostic, 2-severe, 3-moderate, and 4-minimal artifact level. All NUFFT images were 1-non-diagnostic. The five subjects shown at end-diastole represent the range of mean scores at post-exercise stress. Subjects 3–4 are healthy. Subjects 2 and 5 correspond to Subjects 1 and 4 in Fig. 6, accordingly. The mean artifact levels with DRAPR for subjects 1–5 were 2.3, 3.0, 3.0, 3.3 and 3.7, accordingly. The body mass index (BMI) for subjects 1–5 was 32, 38, 23, 29 and 24 lbs/in2, accordingly. The peak heart rate post-exercise for subjects 1–5 was 110, 108, 97, 132, and 135 bpm, accordinglyBack to article page