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k-Wave User Forum » User Favorites: xiangwei xiangwei Support for the k-Wave MATLAB toolbox en-US Wed, 13 May 2026 10:16:47 +0000 http://bbpress.org/?v=1.0.2 <![CDATA[Search]]> q http://www.k-wave.org/forum/search.php Bradley Treeby on "Time reversal reconstruction problem." http://www.k-wave.org/forum/topic/time-reversal-reconstruction-problem#post-5422 Thu, 17 Mar 2016 12:27:54 +0000 Bradley Treeby 5422@http://www.k-wave.org/forum/ HI xiangwei, Which artefacts are unexpected in your reconstruction? Because you only have a very small detector, the images have very strong limited view artefacts. If you've not come across this before, you can read more about these artefacts <a href="http://wweb.uta.edu/faculty/gambarts/med_phys.pdf">here</a>. The feature in the bottom left is just a mirror image of your reconstructed field (you would see the entire grid of absorbers if you expanded the grid). Hope that helps, Brad. xiangwei on "Time reversal reconstruction problem." http://www.k-wave.org/forum/topic/time-reversal-reconstruction-problem#post-5403 Fri, 26 Feb 2016 05:21:55 +0000 xiangwei 5403@http://www.k-wave.org/forum/ I want to get some simulated data using the Kwave and reconstructed by the Time reversal method provided by the toolbox. However, some problem happened in the reconstructed image. There are some unexpected artifact appeared in the image. Could you please tell me why this happens? The following is the related code: close all; clear all; clc; addpath('C:\Program Files\MATLAB\R2013b\toolbox\k-Wave') % ========================================================================= % SETUP THE GRID % ========================================================================= % create the computational grid Nx = 256; % number of grid points in the x (row) direction Ny = 256; % number of grid points in the y (column) direction dx = 0.04e-3; % grid point spacing in the x direction [m] dy = dx; % grid point spacing in the y direction [m] kgrid = makeGrid(Nx, dx, Ny, dy); center_freq = 5e6; % [Hz] bandwidth = 80; % [%] sensor.frequency_response = [center_freq, bandwidth]; % define the properties of the propagation medium medium.sound_speed = 1500; % [m/s] % define the array of time points [s] [kgrid.t_array, dt] = makeTime(kgrid, medium.sound_speed); Nt = round(0.75*length(kgrid.t_array)); kgrid.t_array = (0:Nt-1)*dt; % ========================================================================= % DEFINE A LINEAR ARRAY OF DIRECTIONAL ELEMENTS % ========================================================================= array_left = zeros(Nx, Ny); ut_left_x = 192; i = 1; for ut_left_y = 32:1:64 array_left(ut_left_x, ut_left_y) = 1; ut_left_x = ut_left_x+1; i = i+1; end sensor.mask = array_left; figure, imagesc(sensor.mask); colormap(gray); % ========================================================================= % DEFINE THE SOURCE % ========================================================================= disc_magnitude = 10; % [au] disc_radius = 1; % [grid points] disc_sum = zeros(Nx, Ny); disc_sum_x = zeros(Nx, Ny); disc_sum_y = zeros(Nx, Ny); for disc_y_pos = 64:30:192 disp(num2str(disc_y_pos)); for disc_x_pos = 64:30:192 disc_temp = disc_magnitude*makeDisc(Nx, Ny, disc_x_pos, disc_y_pos, disc_radius); disc_sum_x = disc_temp+ disc_sum_x; end disc_sum_y = disc_sum_x + disc_sum_y; end disc_sum = disc_sum_y; disc_sum_index = find(disc_sum >= 1); disc_sum(disc_sum_index) = 10; figure, imagesc(disc_sum); colormap(gray); source.p0 = disc_sum; % smooth the initial pressure distribution and restore the magnitude % source.p0 = smooth(kgrid, source.p0, true); p0 = source.p0; % ========================================================================= % RUN THE SIMULATION % ========================================================================= PML_size = 30; input_args = {'PMLInside', true, 'PMLSize', PML_size,'Smooth', false, 'PlotPML',false, 'PlotSim', true}; % run the simulation tic sensor_data = kspaceFirstOrder2D(kgrid, medium, source, sensor, input_args{:}); toc %%%%%%%%%%%%%%%%%%%%% Time reversal reconstruction %%%%%%%%%%%%%%%%%%%%%%%% % reset the initial pressure source.p0 = 0; % assign the time reversal data sensor.time_reversal_boundary_data = sensor_data; input_args = {'PMLInside', true, 'PMLSize', PML_size,'Smooth', false, 'PlotPML',false, 'PlotSim', true}; % run the time reversal reconstruction p0_recon = kspaceFirstOrder2D(kgrid, medium, source, sensor, input_args{:}); % add first order compensation for only recording over a half plane p0_recon = p0_recon*2; % plot the initial pressure and sensor distribution obj1 = p0; obj1 = interp2(obj1,2); % figure(1);imshow(obj1,[]); figure; imagesc(kgrid.y_vec*1e3, kgrid.x_vec*1e3, obj1); colormap(hot); colorbar; ylabel('x-position [mm]'); xlabel('y-position [mm]'); axis image; % plot the reconstructed initial pressure img1 = double(p0_recon); img1 = interp2(img1,2); % figure(2);imshow(img1,[]); figure; imagesc(kgrid.y_vec*1e3, kgrid.x_vec*1e3, img1); colormap(hot); colorbar; ylabel('x-position [mm]'); xlabel('y-position [mm]'); axis image; img1_env = abs(hilbert(img1)); figure; imagesc(kgrid.y_vec*1e3, kgrid.x_vec*1e3, img1_env); colormap(hot); colorbar; ylabel('x-position [mm]'); xlabel('y-position [mm]'); axis image; img1_log = 20*log10(img1_env); img1_log = img1_log - max(img1_log(:)); figure; imagesc(kgrid.y_vec*1e3, kgrid.x_vec*1e3, img1_log, [-25,0]); colormap(hot); colorbar; ylabel('x-position [mm]'); xlabel('y-position [mm]'); axis image;