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Abstract #3786

A Parallel Algorithm for Compressed Sensing Dynamic MRI Reconstruction

Loris Cannelli 1 , Paolo Scarponi 1 , Gesualdo Scutari 1 , and Leslie Ying 1

1 Electrical Engineering, University at Buffalo, Buffalo, NY, United States

In this work we present a novel and very general optimization algorithm customized for dynamic MRI reconstruction under the compressed sensing framework. The size of this kind of problems is usually huge: for this reason is compulsory to design algorithms capable to manage a large amount of data in an efficient way. Our approach exploits the benefits of a parallel nature, it relies on a smart decomposition of the original problem and it also possesses the ability of recognizing the elements that will be zero at the solution, taking thus advantage of the sparse structure of the problem itself.

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