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Fig. 1 | Journal of Cardiovascular Magnetic Resonance

Fig. 1

From: Automated segmentation of long and short axis DENSE cardiovascular magnetic resonance for myocardial strain analysis using spatio-temporal convolutional neural networks

Fig. 1

Illustration of the processing pipeline. The first step (orange box) is the segmentation of the left-ventricular (LV) myocardium. It is done manually with DENSEanalysis to obtain training labels, and replaced with a fully automated deep learning (DL) model in this work. Example shown here of an end-systolic short-axis magnitude frame (respectively long-axis) for a healthy subject (A, respectively C) and corresponding ground-truth manual contours (B, respectively D). Lagrangian displacement (E, respectively J) and circumferential (Ecc)/radial (Err)/longitudinal (Ell) strain components (F/H, respectively K/M) are then calculated and strain time curves produced (G/I, respectively L/N)

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