Real-Time Dynamic MRI Reconstruction: Accelerating Compressed Sensing on Graphical Processor Unit

Ankita Shukla, Angshul Majumdar, and Rabab Ward


Magnetic Resonance Imaging, Compressive Sensing, GPU


The aim of this paper is to propose techniques for realtime dynamic MRI reconstruction from partially sampled K-space measurements. Previous techniques in this area are either fast but inaccurate or are slow (therefore not amenable for real-time reconstruction) but with higher degree of accuracy. Recently a Compressed Sensing based algorithm has been proposed which yields high degree of reconstruction accuracy at near real-time speeds. But any attempt to improve one (speed or accuracy) results in reduction of the other. In this work, we propose to improve speed and accuracy of the existing CS algorithm by parallelizing it on a Graphical Processing Unit (GPU). We see that our parallelized dynamic MRI reconstruction algorithm achieves real-time reconstruction speeds and im- proves the reconstruction accuracy at the same time.

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