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Magnetic resonance imaging (MRI) is an essential medical tool with inherentlyslow data acquisition process. Slow acquisition process requires patient to belong time exposed to scanning apparatus. In recent years significant effortsare made towards the applying Compressive Sensing technique to the acquisitionprocess of MRI and biomedical images. Compressive Sensing is an emerging theoryin signal processing. It aims to reduce the amount of acquired data requiredfor successful signal reconstruction. Reducing the amount of acquired imagecoefficients leads to lower acquisition time, i.e. time of exposition to theMRI apparatus. Using optimization algorithms, satisfactory image quality can beobtained from the small set of acquired samples. A number of optimizationalgorithms for the reconstruction of the biomedical images is proposed in theliterature. In this paper, three commonly used optimization algorithms arecompared and results are presented on the several MRI images.

Comparison of Algorithms for Compressed Sensing of Magnetic Resonance Images