From: A deep learning approach for fully automated cardiac shape modeling in tetralogy of Fallot
Parameter | Training/validation set (n = 123) | Test set (n = 30) |
---|---|---|
Imaging | Â | Â |
 Flip angle (°) | 64 (15–80) | 57 (45–81) |
 Phase spatial resolution (mm) | 1.9 (0.9–3.0) | 1.4 (0.5–2.1) |
 Frequency spatial resolution (mm) | 1.6 (0.8–2.8) | 1.4 (0.5–2.1) |
 Slice thickness (mm) | 7.1 (4.0–10.0) | 7.7 (4.5–10.0) |
 Repetition time (ms) | 15.8 (2.6–48.7) | 16.6 (2.7–60.5) |
 Echo time (ms) | 1.4 (1.1–3.3) | 1.4 (1.1–1.8) |
Magnetic field strength | Â | Â |
 1.5T | 120 (98) | 30 (100) |
 3T | 3 (2) | – |
Manufacturer | Â | Â |
 Siemens Healthineers | 55 (45) | 13 (43) |
 Philips Healthcare | 41 (33) | 8 (27) |
 GE Healthcare | 27 (22) | 9 (30) |
Model | Â | Â |
 Siemens Avanto | 55 (45) | 3 (10) |
 Siemens Intera | 41 (33) | 8 (27) |
 GE Discovery MR450 | 14 (11) | 3 (10) |
 GE Signa HDxt | 10 (9) | 1 (3) |
 GE Discovery MR750w | 3 (2) | – |
 Siemens Aera | – | 10 (33) |
 Philips Achieva | – | 3 (10) |
 Philips Ingenia | – | 2 (7) |