  We present a novel automated method to segment the myocardium of both left
and right ventricles in MRI volumes. The segmentation is consistent in 3D
across the slices such that it can be directly used for mesh generation. Two
specific neural networks with multi-scale coarse-to-fine prediction structure
are proposed to cope with the small training dataset and trained using an
original loss function. The former segments a slice in the middle of the
volume. Then the latter iteratively propagates the slice segmentations towards
the base and the apex, in a spatially consistent way. We perform 5-fold
cross-validation on the 15 cases from STACOM to validate the method. For
training, we use real cases and their synthetic variants generated by combining
motion simulation and image synthesis. Accurate and consistent testing results
are obtained.
