Abstract #2640

Unsupervised Tag Removal in Cardiac Tagged MRI using Robust Variational Autoencoder

Botian Xu¹ and John C. Wood^1,2

¹Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States, ²Division of Cardiology, Children's Hospital Los Angeles, Los Angeles, CA, United States

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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