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k-Wave User Forum » User Favorites: zhangguangjie zhangguangjie Support for the k-Wave MATLAB toolbox en-US Wed, 13 May 2026 01:11:11 +0000 http://bbpress.org/?v=1.0.2 <![CDATA[Search]]> q http://www.k-wave.org/forum/search.php Bradley Treeby on "how to use 3D FFT Reconstruction for a real experimental data by Planar Sensor" http://www.k-wave.org/forum/topic/how-to-use-3d-fft-reconstruction-for-a-real-experimental-data-by-planar-sensor-1#post-7345 Wed, 01 Apr 2020 15:11:38 +0000 Bradley Treeby 7345@http://www.k-wave.org/forum/ Hi zhangguangjie, See the help file for <a href="http://www.k-wave.org/documentation/kspacePlaneRecon.php"></a> (or type <code>help kspacePlaneRecon</code> in MATLAB). You don't need to define a computational grid, just the spacing between your data. Brad. zhangguangjie on "how to use 3D FFT Reconstruction for a real experimental data by Planar Sensor" http://www.k-wave.org/forum/topic/how-to-use-3d-fft-reconstruction-for-a-real-experimental-data-by-planar-sensor-1#post-7332 Sun, 29 Mar 2020 16:07:14 +0000 zhangguangjie 7332@http://www.k-wave.org/forum/ Dear Brad I have called the function directly before.But I don't know how define NX NY NZ(computational grid).Because I only know my experiment sensor' dt dy dz. In your example, the dt is automatically generated by kWaveGrid. Bradley Treeby on "how to use 3D FFT Reconstruction for a real experimental data by Planar Sensor" http://www.k-wave.org/forum/topic/how-to-use-3d-fft-reconstruction-for-a-real-experimental-data-by-planar-sensor-1#post-7322 Thu, 26 Mar 2020 11:35:42 +0000 Bradley Treeby 7322@http://www.k-wave.org/forum/ Hi zhangguangjie, What is the problem exactly? Also, is there any reason you have copy and pasted the code from <code>kspacePlaneRecon</code> rather than calling the function directly? Brad zhangguangjie on "how to use 3D FFT Reconstruction for a real experimental data by Planar Sensor" http://www.k-wave.org/forum/topic/how-to-use-3d-fft-reconstruction-for-a-real-experimental-data-by-planar-sensor-1#post-7308 Fri, 20 Mar 2020 07:28:05 +0000 zhangguangjie 7308@http://www.k-wave.org/forum/ Dear sir I learnt the 3D FFT Reconstruction For A Planar Sensor Example and want to use the method to reconstructe my real experimental data.However I can not get right result.My code is as follows： clc clear all close all % start timer tic; % nargin=42; % define defaults num_req_inputs = 5; data_order = 'tyz'; interp_method = '*nearest'; plot_recon = 1; positivity_cond = 1; c = 1500; % The speed of sound fs =25; %MHz Sampling rate dt=1/fs/1000000; dy=0.00135; dz=0.0003; % read data,data order is tyz load('pa_data_all') p=pa_data_all(:,:,:); if strcmp(data_order, 'yzt') p = permute(p, [3 1 2]); end % mirror the time domain data about t = 0 to allow the cosine transform in % the t direction to be computed using an FFT p = [flipdim(p, 1); p(2:end, :, :)]; % extract the size of mirrored input data [Nt, Ny, Nz] = size(p); % update command line status disp('Running k-Wave planar reconstruction...'); disp([' grid size: ' num2str((Nt+1)/2) ' by ' num2str(Ny) ' by ' num2str(Nz) ' grid points']); disp([' interpolation mode: ' interp_method]); % create a computational grid that is evenly spaced in w, ky, and kz, where % Nx = Nt and dx = dt*c kgrid = makeGrid(Nt, dt*c, Ny, dy, Nz, dz); % from the grid for kx, create a computational grid for w using the % relation dx = dt*c; this represents the initial sampling of p(w, ky, kz) w = c*kgrid.kx; % remap the computational grid for kx onto w using the dispersion % relation w/c = (kx^2 + ky^2 + kz^2)^1/2. This gives an w grid that is % evenly spaced in kx. This is used for the interpolation from p(w, ky, kz) % to p(kx, ky, kz). Only real w is taken to force kx (and thus x) to be % symmetrical about 0 after the interpolation. w_new = (c*kgrid.k); % calculate the scaling factor using the value of kx, where % kx = sqrt( (w/c).^2 - kgrid.ky.^2 - kgrid.kz.^2 ) and then manually % replacing the DC value with its limit (otherwise NaN results) sf = c^2*sqrt( (w/c).^2 - kgrid.ky.^2 - kgrid.kz.^2)./(2*w); sf(w == 0 & kgrid.ky == 0 & kgrid.kz == 0) = c/2; % compute the FFT of the input data p(t, y, z) to yield p(w, ky, kz) and % scale p = sf.*fftshift(fftn(fftshift(p))); % remove unused variables % clear sf; % exclude the inhomogeneous part of the wave p(abs(w) < (c*sqrt(kgrid.ky.^2 + kgrid.kz.^2))) = 0; % compute the interpolation from p(w, ky, kz) to p(kx, ky, kz); for a % matrix indexed as [M, N, P], the axis variables must be given in the % order N, M, P p = interp3(kgrid.ky, w, kgrid.kz, p, kgrid.ky, w_new, kgrid.kz, interp_method); % remove unused variables % clear kgrid w; % set values outside the interpolation range to zero p(isnan(p)) = 0; % compute the inverse FFT of p(kx, ky, kz) to yield p(x, y, z) p = real(ifftshift(ifftn(ifftshift(p)))); % remove the left part of the mirrored data which corresponds to the % negative part of the mirrored time data p = p( (Nt + 1)/2:Nt, :, :); % correct the scaling - the forward FFT is computed with a spacing of dt % and the reverse requires a spacing of dz = dt*c, the reconstruction % assumes that p0 is symmetrical about z, and only half the plane collects % data (first approximation to correcting the limited view problem) (p_zxy) p = 2*2*p./c; % enfore positivity condition (p_zxy) if positivity_cond disp(' applying positivity condition...'); p(p < 0) = 0; end % update command line status disp([' computation completed in ' scaleTime(toc)]); % plot the reconstruction if plot_recon % allocate axis dimensions x_axis = [0 (Nt/2)*dt*c]; y_axis = [0 Ny*dy]; z_axis = [0 Nz*dz]; % select suitable axis scaling factor [x_sc, scale, prefix] = scaleSI(max([(Nt/2)*dt*c, Ny*dy, Nz*dz])); % select suitable plot scaling factor plot_scale = max(p(:)); % create the figures figure; subplot(2, 2, 1), imagesc(y_axis*scale, x_axis*scale, squeeze(p(:, :, round(end/2))), [-plot_scale, plot_scale]); axis image; title('x-y plane'); subplot(2, 2, 2), imagesc(z_axis*scale, x_axis*scale, squeeze(p(:, round(end/2), :)), [-plot_scale, plot_scale]); axis image; xlabel(['(All axes in ' prefix 'm)']); title('x-z plane'); subplot(2, 2, 3), imagesc(z_axis*scale, y_axis*scale, squeeze(p(round(end/2), :, :)), [-plot_scale, plot_scale]); axis image; title('y-z plane'); colormap(getColorMap); end Thank you Sir. Sincerely Bradley Treeby on "Provision for acoustic wave generation from absorption profile of a 3d tissue." http://www.k-wave.org/forum/topic/provision-for-acoustic-wave-generation-from-absorption-profile-of-a-3d-tissue#post-6614 Mon, 29 Oct 2018 11:23:10 +0000 Bradley Treeby 6614@http://www.k-wave.org/forum/ Hi Prabhakar, If your laser pulse is short enough to assume that stress confinement holds, you can directly assign the absorbed energy distribution from your Monte-Carlo simulation to <code>source.p0</code>. Note, you will need to multiply by the Gruneisen parameter if you care about absolute values of pressure (e.g., see <a href="https://doi.org/10.1121/1.1920227">here</a>). Brad prabhakar.amarana on "Provision for acoustic wave generation from absorption profile of a 3d tissue." http://www.k-wave.org/forum/topic/provision-for-acoustic-wave-generation-from-absorption-profile-of-a-3d-tissue#post-6605 Thu, 25 Oct 2018 09:45:09 +0000 prabhakar.amarana 6605@http://www.k-wave.org/forum/ Dear Sir, I am working on breast cancer detection through simulation of photoacoustic imaging. Before k-wave simulation, I have done the simulation of light propagation inside the breast tissue model through 3d Monte-Carlo simulation. 3d absorption profile obtained from this simulation was used as a source in the k-wave simulation. Acoustic wave propagation through the medium and its detection using planar array were achieved with k-wave. But I wanted to know whether it is correct to place the absorption profile as a source in the k-wave simulation? I am also eager to find any mechanism or provision to generate acoustic wave from the absorption profile in the k-wave toolbox so that this generated acoustic wave will become a source in the k-wave simulation.