MR Image Reconstruction

Contact person: Dr. Manuel Desco

Magnetic Resonance Imaging (MRI) is a biomedical imaging modality with outstanding features such as excellent soft tissue contrast and very high spatial resolution. Despite its great properties, MRI suffers from some drawbacks, such as low sensitivity and long acquisition times.

Compressed sensing is a novel technique that enables the reduction of acquisition times and can also improve spatiotemporal resolution and image quality. Compressed sensing enables the reconstruction of images from an incomplete number of acquired samples, provided that 1) the images to reconstruct have a sparse representation in a certain domain, 2) the undersampling applied is random and 3) specific non-linear reconstruction algorithms are used.

Moreover, not only medical images are typically sparse, but also the higher the dimensionality of the measurements, the higher the acceleration that can be achieved, and cardiac cine MRI and fMRI are good examples due to their temporal redundancy.

In our group we have developed and tested new algorithms for the reconstruction of compressed dynamic MRI studies, and implemented the solution in our Bruker Biospin 7T scanner.

Selected Articles


P Montesinos, JR Polimeni, B Bilgic, SF Cauley, M Desco, R Nezafat, LL Wald, E Adalsteinsson, DE Sosnovik. "High Resolution Inner Volume Imaging of Human Coronary Atherosclerotic Plaque: Impact and Limits of Parallel Acquisition" (In preparation)

P Montesinos, H Seifarth, H Bhat, M Desco, F A Jaffe, E Adalsteinsson, U Hoffmann,  R Nezafat, D E Sosnovik. “Motion, Resolution and Noise Thresholds for the Accurate Classification of Human Coronary Atherosclerotic Plaque”. (Submitted to JCMR)

JFPJ Abascal*, P Montesinos*, E Marinetto, J Pascau, M Desco. "Comparison of total variation with a motion estimation based compressed sensing approach for self-gated cardiac cine MRI in small animal studies". PLoS One, 9(10): e110594 (10 pp.), 2014

P Montesinos, JF PJ Abascal, L Cussó, JJ Vaquero, M Desco. "Application of the Compressed Sensing Technique to Self-Gated Cardiac Cine Sequences in Small Animals". Magnetic Resonance in Medicine, 72(2): 369-380, 2013

Chavarrias, C., Abascal, J.F., Montesinos, P. and Desco, M.,"Exploitation of temporal redundancy in compressed sensing reconstruction of fMRI studies with a prior-based algorithm (PICCS)". Med Phys,  42(7): p. 3814 (2015).

Funded Grants


 

Related Research Lines


Preclinic Research

Cardiology Lorena Cussó

Technological Development 

Imagen por Rayos X Mónica Abella