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Abstract #4867

Adaptive Compressed Sensing MRI

Ricardo Otazo1, Daniel K. Sodickson1

1Center for Biomedical Imaging, New York University School of Medicine, New York, NY, United States

A method to adapt the sparsifying transform in order to increase image sparsity for compressed sensing (CS) is presented. The method updates the sparsifying transform and computes the corresponding sparse coefficient simultaneously using image examples from the undersampled data. We demonstrate improved performance of adaptive CS over standard CS with a pre-defined wavelet transform on a brain imaging example