Prospective acceleration of diffusion tensor imaging with compressed sensing using adaptive dictionaries

Diffusion MRI requires acquisition of multiple diffusion‐weighted images, resulting in long scan times. Here, we investigate combining compressed sensing and a fast imaging sequence to dramatically reduce acquisition times in cardiac diffusion MRI.

[1]  R L Winslow,et al.  Direct histological validation of diffusion tensor MRI in formaldehyde‐fixed myocardium , 2000, Magnetic resonance in medicine.

[2]  R. Tibshirani Regression Shrinkage and Selection via the Lasso , 1996 .

[3]  Jean-Philippe Thiran,et al.  Sparse regularization for fiber ODF reconstruction: from the suboptimality of $\ell_2$ and $\ell_1$ priors to $\ell_0$ , 2012, 1208.2247.

[4]  C. Hardy,et al.  Accelerated diffusion spectrum imaging in the human brain using compressed sensing , 2011, Magnetic resonance in medicine.

[5]  Peter Kohl,et al.  Histo-anatomical structure of the living isolated rat heart in two contraction states assessed by diffusion tensor MRI , 2012, Progress in biophysics and molecular biology.

[6]  Suyash P. Awate,et al.  Compressed sensing HARDI via rotation-invariant concise dictionaries, flexible K-space undersampling, and multiscale spatial regularity , 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging.

[7]  C. Beaulieu,et al.  Reduction of ringing and blurring artifacts in fast spin‐echo imaging , 1993, Journal of magnetic resonance imaging : JMRI.

[8]  C S Henriquez,et al.  Myocardial fiber orientation mapping using reduced encoding diffusion tensor imaging. , 2001, Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance.

[9]  L. Ying,et al.  Accelerated MR diffusion tensor imaging using distributed compressed sensing , 2014, Magnetic resonance in medicine.

[10]  Shaohua Wu,et al.  Compressed sensing on DTI via rotating interpolation , 2013, 2013 IEEE International Conference of IEEE Region 10 (TENCON 2013).

[11]  Elizabeth M Tunnicliffe,et al.  Accelerated human cardiac diffusion tensor imaging using simultaneous multislice imaging , 2015, Magnetic resonance in medicine.

[12]  Rachid Deriche,et al.  Continuous diffusion signal, EAP and ODF estimation via Compressive Sensing in diffusion MRI , 2013, Medical Image Anal..

[13]  Joel A. Tropp,et al.  Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit , 2007, IEEE Transactions on Information Theory.

[14]  Brandon Whitcher,et al.  Using the wild bootstrap to quantify uncertainty in diffusion tensor imaging , 2008, Human brain mapping.

[15]  M. Elad,et al.  $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation , 2006, IEEE Transactions on Signal Processing.

[16]  Mathews Jacob,et al.  Acceleration of high angular and spatial resolution diffusion imaging using compressed sensing with multichannel spiral data , 2015, Magnetic resonance in medicine.

[17]  D. Donoho,et al.  Sparse MRI: The application of compressed sensing for rapid MR imaging , 2007, Magnetic resonance in medicine.

[18]  R. Deriche,et al.  Design of multishell sampling schemes with uniform coverage in diffusion MRI , 2013, Magnetic resonance in medicine.

[19]  Maxime Descoteaux,et al.  Denoising and fast diffusion imaging with physically constrained sparse dictionary learning , 2014, Medical Image Anal..

[20]  M. Descoteaux,et al.  Sparsity Characterisation of the Diffusion Propagator , 2010 .

[21]  Ganesh Adluru,et al.  Constrained Reconstruction of Sparse Cardiac MR DTI Data , 2007, FIMH.

[22]  Stephen P. Boyd,et al.  Enhancing Sparsity by Reweighted ℓ1 Minimization , 2007, 0711.1612.

[23]  Stefan Skare,et al.  The presence of two local myocardial sheet populations confirmed by diffusion tensor MRI and histological validation , 2011, Journal of magnetic resonance imaging : JMRI.

[24]  Guillermo Sapiro,et al.  Online Learning for Matrix Factorization and Sparse Coding , 2009, J. Mach. Learn. Res..

[25]  Emmanuel Flachaire,et al.  The wild bootstrap, tamed at last , 2001 .

[26]  Xiaoping Hu,et al.  PCLR: Phase‐constrained low‐rank model for compressive diffusion‐weighted MRI , 2014, Magnetic resonance in medicine.

[27]  H. Gudbjartsson,et al.  The rician distribution of noisy mri data , 1995, Magnetic resonance in medicine.

[28]  A. Bruckstein,et al.  K-SVD : An Algorithm for Designing of Overcomplete Dictionaries for Sparse Representation , 2005 .

[29]  Julien Cohen-Adad,et al.  Accelerated diffusion spectrum imaging with compressed sensing using adaptive dictionaries , 2012, MICCAI.

[30]  Jerry L. Prince,et al.  Resolution of crossing fibers with constrained compressed sensing using diffusion tensor MRI , 2012, NeuroImage.

[31]  Ganesh Adluru,et al.  Model‐based reconstruction of undersampled diffusion tensor k‐space data , 2013, Magnetic resonance in medicine.

[32]  G Allan Johnson,et al.  Reduction of artifacts in T2‐weighted PROPELLER in high‐field preclinical imaging , 2011, Magnetic resonance in medicine.

[33]  Pierre Croisille,et al.  Low b-Value Diffusion-Weighted Cardiac Magnetic Resonance Imaging: Initial Results in Humans Using an Optimal Time-Window Imaging Approach , 2011, Investigative radiology.

[34]  P. Basser,et al.  MR diffusion tensor spectroscopy and imaging. , 1994, Biophysical journal.

[35]  R. Deriche,et al.  Comparison of sampling strategies and sparsifying transforms to improve compressed sensing diffusion spectrum imaging , 2015, Magnetic resonance in medicine.

[36]  Yogesh Rathi,et al.  Spatially Regularized Compressed Sensing for High Angular Resolution Diffusion Imaging , 2011, IEEE Transactions on Medical Imaging.

[37]  E. Aboussouan,et al.  Non-Cartesian Compressed Sensing for Diffusion Spectrum Imaging , 2010 .