SIAT_MRIdata200
200 Data for MRI Reconstruction
% The dataset was provided by Shenzhen Institutes of Advanced Technology, the Chinese Academy of Science.
% Some of them are used in the following papers:
% M. Zhang, M. Li, J. Zhou, Y, Zhu, S. Wang, D. Liang, Y. Chen, Q. Liu. High-dimensional embedding network derived prior for compressive sensing MRI reconstruction, Med. Image Anal., vol. xx, pp.1-27, 2020.
% Q. Liu, Q. Yang, H. Cheng, S. Wang, M. Zhang, D. Liang, Highly undersampled magnetic resonance imaging reconstruction using autoencoding priors, Magn. Reson. Med., vol. 83, no. 1, pp. 322-336, 2020.
% Y. Liu, Q. Liu, M. Zhang, Q. Yang, S. Wang, D. Liang. IFR-Net: Iterative feature refinement network for compressed sensing MRI, IEEE Trans. Comput. Imag., vol. 6, pp. 434-446, 2020.
% S. Li, J. Zhou, D. Liang, Q. Liu, MRI denoising using progressively distribution-based neural network, Magn. Reson. Imaging, 2020. https://doi.org/10.1016/j.mri.2020.04.006.
%% #######%%%%% read test data3 %%%%
% The original data is the size of 270x256 or 256x270. You need to clip it to be 256x256.
%load lsq28; Img = imrotate(Img, -90); Img(:,end-6:end) = []; Img(:,1:7) = [];
%load lsq68; Img = imrotate(Img, 90); Img(:,end-6:end) = []; Img(:,1:7) = [];
%load lsq200; Img = imrotate(Img, 90); Img(:,end-6:end) = []; Img(:,1:7) = [];
load lsq196; Img = imrotate(Img, 90); Img(:,end-6:end) = []; Img(:,1:7) = [];
gt = Img./max(abs(Img(:)));
figure(334);imshow([real(gt),imag(gt),abs(gt)],[]);
%% #######%%%%% display data20 %%%%
index = 1:10:200;
ddd1 = [];ddd2 = [];
for ii =1:10
load(['lsq',num2str(index(ii)),'.mat']);Img = Img./max(abs(Img(:))); ddd1 = [ddd1,Img];
load(['lsq',num2str(index(10+ii)),'.mat']);Img = Img./max(abs(Img(:))); ddd2 = [ddd2,Img];
end
ddd1 = [ddd1;ddd2];
figure(600);imshow(abs(ddd1),[]);
%% #######%%%%% read test data200 %%%%
for ii =1:200
load(['lsq',num2str(ii),'.mat']);
figure(1000);
subplot(1,2,1),imshow(abs(Img),[]);colorbar;
Img = Img./max(abs(Img(:)));
subplot(1,2,2),imshow(abs(Img),[]);colorbar;
end
Visual illustration of the Real and Imaginary component
Left：Real component, Middle: Imaginary component, Right: Magntitude image.
Visual illustration of 20 data
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