demo_tpsf

add imshow3 convenience function
general params
params for generating the mask
Simulate ideal system input
Simulate center-out ordering
Simulate randomly shuffled ordering

%%%%%%
% This code demonstrates the T2 Shuffling transform point spread functions (PSF)
% described in the MRM paper,
% "T2 Shuffling: Sharp, Multi-Contrast, Volumetric Fast Spin-Echo Imaging"
%
% The code is provided to demonstrate the method. It is not optimized
% for reconstruction time
%
% Jonathan Tamir <jtamir@eecs.berkeley.edu>
% Jan 04, 2015

addpath src/utils

basis = squeeze(readcfl('data/knee/bas'));
T = size(basis, 1);

Size: 1   1   1   1   1  80  80

add imshow3 convenience function

imshow3 = @(im) montage(reshape(abs(im), size(im, 1), size(im,2), 1, []), [min(abs(im(:))), max(abs(im(:)))]);

general params

ny = 256;
nz = 256;
K = 4;
patch_size = 7;

params for generating the mask

mask_options.dims = [ny, nz];
mask_options.accel = [1, 1];
mask_options.ETL = T;
mask_options.e2s = 0;
mask_options.cut_corners = false;
mask_options.num_masks = 1;
mask_options.VD = 1;
mask_options.mask_cal_size = 32;

Simulate ideal system input

The ideal system input is a patch in each active temporal coefficient

mask = ones(ny, nz, T);
TPSF_ideal = tpsf(mask, basis, K, patch_size);
figure(1);
imshow3(TPSF_ideal), colormap('default');
ftitle('Ideal system input', 32);

Simulate center-out ordering

The TPSF from center-out ordering shows blurring, and the coefficients are coupled

mask_options.shuffle = false;
mask = gen_t2shuffling_mask(mask_options);
TPSF_cent = tpsf(mask, basis, K, patch_size);
figure(2);
imshow3(TPSF_cent), colormap('default');
ftitle('Center-out TPSF', 32);

Simulate randomly shuffled ordering

The TPSF from randomly shuffled ordering shows a sharp peak, with incoherent artifacts that look like noise