T2 Shuffling Demonstration Code
Demonstration code for the MRM manuscript, T2 Shuffling: Sharp, Multi-Contrast, Volumetric Fast Spin-Echo Imaging .
Written by Jon Tamir. Please feel free to contact me or post an issue on the repository page if there is a problem.
This code may be freely used and modified for educational, research, and not-for-profit purposes (See
LICENSE for more information).
T2 Shuffling is an MRI acquisition and reconstruction method based on 3D Fast Spin-Echo. The method accounts for temporal dynamics during the echo trains to reduce image blur and resolve multiple image contrasts along the T2 relaxation curve. Figure 1 provides a high level overview of the method. The echo train ordering is randomly shuffled during the acquisition according to variable density Poisson disc sampling masks. The shuffling leads to reduced image blur at the cost of noise-like artifacts. The artifacts are iteratively suppressed in a regularized reconstruction based on compressed sensing and full signal dynamics are recovered.
 J.I. Tamir, M. Uecker, W. Chen, P. Lai, M.T. Alley, S.S. Vasanawala, and M. Lustig, T2 Shuffling: Sharp, multicontrast, volumetric fast spin-echo imaging. Magn Reson Med 2016 (Early View). doi: 10.1002/mrm.26102
src/: Matlab demos, outlined below
src/utils/: Matlab utility and mex functions
data/: Collection of mat and BART files used by the demos
doc/: Documentation and demos
To install the mex files and add the correct paths for the demos,
navigate to the
t2shuffling-support base directory, and run the command
Now you can run any of the demos in the
src directory. To list the demos, run
src/demo_t2shuffling_recon.m demonstrates the T2 Shuffling reconstruction on an axial slice of an
src/demo_gen_subspace.m demonstrates the T2 Shuffling reconstruction on an axial slice of an
src/demo_llr_degrees_of_freedom.m demonstrates the LLR degrees of freedom and k-means clustering.
src/demo_t2shuffling_mask.m demonstrates the echo train view ordering/sampling pattern generation.
src/demo_b1_and_model_error.m simulates the subspace model error as a function of percent B1 inhomogeneity and T2 value,
as well as demonstrating the bias vs. noise tradeoff with subspace size.
src/demo_psf_1d.m simulates the 1D point spread function (PSF) for exponential decay
with both ceter-out and randomly shuffled view orderings.
src/demo_tpsf.m simulates the transform point spread function (TPSF) for a center-out
ordering and a randomly shuffled ordering.
The extended phase graph (EPG) code was written by Brian Hargreaves and downloaded from http://web.stanford.edu/~bah/software/epg/ on Dec. 7, 2015.
Some Matlab utility functions were written by Michael Lustig in the ESPIRiT Matlab reference implementation. They were downloaded from http://people.eecs.berkeley.edu/~mlustig/Software.html on Dec. 7, 2015.
All rights/distribution are the same as for the original code, and should cite the original author and webpage