Reducción de los tiempos de adquisición de imágenes por resonancia magnética utilizando técnicas de compressed sensing

Abstract

Introduction: The acquisition process in Magnetic Resonance Images (MRI) is slow. One approach to reduce the acquisition times is the reconstruction of undersampled data. i.e. to acquire less samples that those needed for standard application, and to reconstruct the unknown samples using mathematical algorithms. We propose to used reconstruction techniques for undersampled data based on Compressed Sensing (CS) to decrease the acquisition times, obtaining identical MRI as those obtained with all samples. Methods: We performed reconstructions of undersampled data obtained from phantoms and MRI with 60%, 55% and 50% of the samples. Results: When the number of samples was more that the double of pixels with non cero intensity, the reconstructions where identical to the original ones. For the MRI experiment, this was achieved with 60% of the samples, therefore obtaining a 40% of reduction in the acquisition time. Discussion: Our reconstruction technique based on CS is an effective way for reducing the acquisition times in MRI.