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diff --git a/demo/Demo2.m b/demo/Demo2.m new file mode 100644 index 0000000..3c1592c --- /dev/null +++ b/demo/Demo2.m @@ -0,0 +1,156 @@ +% Demonstration of tomographic reconstruction from noisy and corrupted by +% artifacts undersampled projection data using Students t penalty +% This is the missing wedge demo, run it after DemoFISTA_StudT + +% see ReadMe file for instructions +% clear all +% close all + +load phantom_bone512.mat % load the phantom +load my_red_yellowMAP.mat % load the colormap +% load sino1.mat; % load noisy sinogram + +N = 512; % the size of the tomographic image NxN +theta = 1:1:180; % acquisition angles (in parallel beam from 0 to Pi) +theta_rad = theta*(pi/180); % conversion to radians +P = 2*ceil(N/sqrt(2))+1; % the size of the detector array +ROI = find(phantom > 0.0); + +add_wedges % apply the missing wedge mask + +%% +fprintf('%s\n', 'Direct reconstruction using FBP...'); +FBP_1 = iradon(MW_sino_artifacts', theta, N); + +fprintf('%s %.4f\n', 'RMSE for FBP reconstruction:', RMSE(FBP_1(:), phantom(:))); + +figure(1); +% set(gcf, 'Position', get(0,'Screensize')); +subplot_tight(1,2,1, [0.05 0.05]); imshow(FBP_1,[-2 0.8]); title('FBP reconstruction of noisy and corrupted by artifacts sinogram'); colorbar; +subplot_tight(1,2,2, [0.05 0.05]); imshow((phantom - FBP_1).^2,[0 0.1]); title('residual: (ideal phantom - FBP)^2'); colorbar; +colormap(cmapnew); +%% +fprintf('%s\n', 'Reconstruction using FISTA-LS without regularization...'); +clear params +% define parameters +params.sino = MW_sino_artifacts; +params.N = N; % image size +params.angles = theta_rad; % angles in radians +params.iterFISTA = 132; %max number of outer iterations +params.X_ideal = phantom; % ideal phantom +params.ROI = ROI; % phantom region-of-interest +params.show = 0; % visualize reconstruction on each iteration +params.slice = 1; params.maxvalplot = 0.6; +params.weights = Dweights; % statistical weighting +tic; [X_FISTA, error_FISTA, obj_FISTA, sinoFISTA] = FISTA_REC(params); toc; + +fprintf('%s %.4f\n', 'Min RMSE for FISTA-LS reconstruction:', min(error_FISTA(:))); + +figure(2); clf +%set(gcf, 'Position', get(0,'Screensize')); +subplot_tight(1,2,1, [0.05 0.05]); imshow(X_FISTA,[0 0.6]); title('FISTA-LS reconstruction'); colorbar; +subplot_tight(1,2,2, [0.05 0.05]); imshow((phantom - X_FISTA).^2,[0 0.1]); title('residual'); colorbar; +colormap(cmapnew); +figure(3); clf +subplot_tight(1,2,1, [0.05 0.05]); plot(error_FISTA); title('RMSE plot'); colorbar; +subplot_tight(1,2,2, [0.05 0.05]); plot(obj_FISTA); title('Objective plot'); colorbar; +colormap(cmapnew); +%% +fprintf('%s\n', 'Reconstruction using FISTA-LS-TV...'); +clear params +% define parameters +params.sino = MW_sino_artifacts; +params.N = N; % image size +params.angles = theta_rad; % angles in radians +params.iterFISTA = 200; % max number of outer iterations +params.lambdaTV = 5.39e-05; % regularization parameter for TV problem +params.tol = 1.0e-04; % tolerance to terminate TV iterations +params.iterTV = 20; % the max number of TV iterations +params.X_ideal = phantom; % ideal phantom +params.ROI = ROI; % phantom region-of-interest +params.weights = Dweights; % statistical weighting +params.show = 0; % visualize reconstruction on each iteration +params.slice = 1; params.maxvalplot = 0.6; +tic; [X_FISTA_TV, error_FISTA_TV, obj_FISTA_TV, sinoFISTA_TV] = FISTA_REC(params); toc; + +fprintf('%s %.4f\n', 'Min RMSE for FISTA-LS-TV reconstruction:', min(error_FISTA_TV(:))); + +figure(4); clf +subplot_tight(1,2,1, [0.05 0.05]); imshow(X_FISTA_TV,[0 0.6]); title('FISTA-LS-TV reconstruction'); colorbar; +subplot_tight(1,2,2, [0.05 0.05]); imshow((phantom - X_FISTA_TV).^2,[0 0.1]); title('residual'); colorbar; +colormap(cmapnew); +figure(5); clf +subplot_tight(1,2,1, [0.05 0.05]); plot(error_FISTA_TV); title('RMSE plot'); colorbar; +subplot_tight(1,2,2, [0.05 0.05]); plot(obj_FISTA_TV); title('Objective plot'); colorbar; +colormap(cmapnew); +%% +fprintf('%s\n', 'Reconstruction using FISTA-GH-TV...'); +clear params +% define parameters +params.sino = MW_sino_artifacts; +params.N = N; % image size +params.angles = theta_rad; % angles in radians +params.iterFISTA = 250; % max number of outer iterations +params.lambdaTV = 0.0019; % regularization parameter for TV problem +params.tol = 1.0e-04; % tolerance to terminate TV iterations +params.iterTV = 20; % the max number of TV iterations +params.X_ideal = phantom; % ideal phantom +params.ROI = ROI; % phantom region-of-interest +params.weights = Dweights; % statistical weighting +params.lambdaR_L1 = 0.002; % parameter to sparsify the "rings vector" +params.show = 0; % visualize reconstruction on each iteration +params.slice = 1; params.maxvalplot = 0.6; +tic; [X_FISTA_GH_TV, error_FISTA_GH_TV, obj_FISTA_GH_TV, sinoFISTA_GH_TV] = FISTA_REC(params); toc; + +fprintf('%s %.4f\n', 'Min RMSE for FISTA-GH-TV reconstruction:', min(error_FISTA_GH_TV(:))); + +figure(6); clf +subplot_tight(1,2,1, [0.05 0.05]); imshow(X_FISTA_GH_TV,[0 0.6]); title('FISTA-GH-TV reconstruction'); colorbar; +subplot_tight(1,2,2, [0.05 0.05]);imshow((phantom - X_FISTA_GH_TV).^2,[0 0.1]); title('residual'); colorbar; +colormap(cmapnew); + +figure(7); clf +subplot_tight(1,2,1, [0.05 0.05]); plot(error_FISTA_GH_TV); title('RMSE plot'); colorbar; +subplot_tight(1,2,2, [0.05 0.05]); plot(obj_FISTA_GH_TV); title('Objective plot'); colorbar; +colormap(cmapnew); +%% +fprintf('%s\n', 'Reconstruction using FISTA-Student-TV...'); +clear params +% define parameters +params.sino = MW_sino_artifacts; +params.N = N; % image size +params.angles = theta_rad; % angles in radians +params.iterFISTA = 80; % max number of outer iterations +% params.L_const = 80000; % Lipshitz constant (can be chosen manually to accelerate convergence) +params.lambdaTV = 0.0016; % regularization parameter for TV problem +params.tol = 1.0e-04; % tolerance to terminate TV iterations +params.iterTV = 20; % the max number of TV iterations +params.X_ideal = phantom; % ideal phantom +params.ROI = ROI; % phantom region-of-interest +params.weights = Dweights; % statistical weighting +params.fidelity = 'student'; % selecting students t fidelity +params.show = 0; % visualize reconstruction on each iteration +params.slice = 1; params.maxvalplot = 0.6; +tic; [X_FISTA_student_TV, error_FISTA_student_TV, obj_FISTA_student_TV, sinoFISTA_student_TV] = FISTA_REC(params); toc; + +fprintf('%s %.4f\n', 'Min RMSE for FISTA-Student-TV reconstruction:', min(error_FISTA_student_TV(:))); + +figure(8); +set(gcf, 'Position', get(0,'Screensize')); +subplot_tight(1,2,1, [0.05 0.05]); imshow(X_FISTA_student_TV,[0 0.6]); title('FISTA-Student-TV reconstruction'); colorbar; +subplot_tight(1,2,2, [0.05 0.05]); imshow((phantom - X_FISTA_student_TV).^2,[0 0.1]); title('residual'); colorbar; +colormap(cmapnew); + +figure(9); +subplot_tight(1,2,1, [0.05 0.05]); plot(error_FISTA_student_TV); title('RMSE plot'); colorbar; +subplot_tight(1,2,2, [0.05 0.05]); plot(obj_FISTA_student_TV); title('Objective plot'); colorbar; +colormap(cmapnew); +%% +% print all RMSE's +fprintf('%s\n', '--------------------------------------------'); +fprintf('%s %.4f\n', 'RMSE for FBP reconstruction:', RMSE(FBP_2(:), phantom(:))); +fprintf('%s %.4f\n', 'Min RMSE for FISTA-LS reconstruction:', min(error_FISTA(:))); +fprintf('%s %.4f\n', 'Min RMSE for FISTA-LS-TV reconstruction:', min(error_FISTA_TV(:))); +fprintf('%s %.4f\n', 'Min RMSE for FISTA-GH-TV reconstruction:', min(error_FISTA_GH_TV(:))); +fprintf('%s %.4f\n', 'Min RMSE for FISTA-Student-TV reconstruction:', min(error_FISTA_student_TV(:))); +%
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