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Abstract #4139

MR Image Reconstruction via Denoising (MR-RED)

Adam Rich1 and Rizwan Ahmad1

1Department of Biomedical Engineering, The Ohio State University, Columbus, OH, United States

In this work, the feasibility of employing denoising to recover MR images from undersampled data is demonstrated. By embedding denoisers into the Laplacian-based regularization functional and solving the resulting optimization problem, state-of-the-art results are achieved. Performance of several denoisers and compressed sensing methods is compared in four cardiac MRI datasets. We show that denoising-based reconstruction can outperform soft-thresholding-based algorithms in terms of normalized MSE.

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