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Fast Low Rank column-wise Compressive Sensing for Accelerated Dynamic MRI
Conference proceeding

Fast Low Rank column-wise Compressive Sensing for Accelerated Dynamic MRI

Silpa Babu, Wahidul Alam, Sajan Goud Lingala and Namrata Vaswani
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (Singapore)
04/27/2022
DOI: 10.1109/ICASSP43922.2022.9747549

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Abstract

In recent work we developed a fast and sample-efficient gradient descent (GD) solution to the following "Low Rank column-wise Compressive Sensing (LRcCS)": recover an n × q, rank-r matrix X* from measurements yk=Akx∗k, k=1,2,…,q when each yk is an m-length vector with m < n, and the rank r ≪ min(n,q). Accelerated dynamic MRI is a key application where this problem occurs. In this work, we show the power of our approach (and of its modification for the MRI setting) for four very different highly undersampled dynamic MRI applications. Without any application-specific parameter tuning, in most settings, our approach outperforms the state-of-the-art MRI methods, while also being significantly faster in all settings.

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