We propose a method for synthesizing cardiac MR images with plausible heart shape and realistic appearance. It breaks down the synthesis into labels deformation and label-to-image translation. The former is achieved via latent space interpolation in a VAE model, while the latter is accomplished via a conditional GAN model. We synthesize 32 short-axis slices within each subject (intrasubject), as well as eight intermediary generated subjects between two dissimilar real subjects (intersubject) that have different anatomies. Such method could provide a solution to enrich a database and to pave the way for the development of generalizable DL based algorithms.
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