Post processing of cardiac tagged MRI has always been challenging because of poor SNR and image artifact. Inspired by unsupervised anomalies detection using variational autoencoder (VAE), we treat tags as anomalies and employ robust variational autoencoder (RVAE), using \(\beta\)-ELBO cost, which is more robust to outliers, to replace the log-likelihood optimization of a prototypical VAE, to generate tag-free results from cardiac tagged images.
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