k-Wave User Forum » Topic: Photoacoustic tomography reconstruction (delay and sum)

k-Wave User Forum » Topic: Photoacoustic tomography reconstruction (delay and sum) http://www.k-wave.org/forum/topic/photoacoustic-tomography-reconstruction-delay-and-sum Support for the k-Wave MATLAB toolbox en-US Fri, 15 May 2026 10:39:23 +0000 http://bbpress.org/?v=1.0.2 <![CDATA[Search]]> q http://www.k-wave.org/forum/search.php leoliu5168 on "Photoacoustic tomography reconstruction (delay and sum)" http://www.k-wave.org/forum/topic/photoacoustic-tomography-reconstruction-delay-and-sum#post-8082 Tue, 09 Mar 2021 19:23:27 +0000 leoliu5168 8082@http://www.k-wave.org/forum/ Hello everyone I'm trying to simulate delay and sum in photoacoustic tomography. I've set the initial pressure and medium. I would like to know how to calculate time delay and reconstruct the image from sensor data. If possible, please give me some sample codes. Thanks for helping me. clearvars; close all; % ========================================================================= % SIMULATION % ========================================================================= % create the computational grid Nx = 128; % number of grid points in the x (row) direction Ny = 128; % number of grid points in the y (column) direction dx = 0.1e-3; % grid point spacing in the x direction [m] dy = 0.1e-3; % grid point spacing in the y direction [m] kgrid = kWaveGrid(Nx, dx, Ny, dy); % define the properties of the propagation medium medium.sound_speed = 1500; % [m/s] medium.alpha_coeff = 0.75; % [dB/(MHz^y cm)] medium.alpha_power = 1.5; % create initial pressure distribution using makeDisc disc_magnitude = 5; % [Pa] disc_x_pos = 50; % [grid points] disc_y_pos = 50; % [grid points] disc_radius = 8; % [grid points] disc_1 = disc_magnitude * makeDisc(Nx, Ny, disc_x_pos, disc_y_pos, disc_radius); disc_magnitude = 3; % [Pa] disc_x_pos = 80; % [grid points] disc_y_pos = 60; % [grid points] disc_radius = 5; % [grid points] disc_2 = disc_magnitude * makeDisc(Nx, Ny, disc_x_pos, disc_y_pos, disc_radius); disc_magnitude = 1; % [Pa] disc_x_pos = 50; % [grid points] disc_y_pos = 80; % [grid points] disc_radius = 3; % [grid points] disc_3 = disc_magnitude * makeDisc(Nx, Ny, disc_x_pos, disc_y_pos, disc_radius); source.p0 = disc_1 + disc_2+ disc_3; % define a centered circular sensor sensor_radius = 4e-3; % [m] num_sensor_points = 50; sensor.mask = makeCartCircle(sensor_radius, num_sensor_points); % run the simulation sensor_data = kspaceFirstOrder2D(kgrid, medium, source, sensor); % plot the initial pressure and sensor distribution figure; imagesc(kgrid.y_vec * 1e3, kgrid.x_vec * 1e3, source.p0 + cart2grid(kgrid, sensor.mask), [-1, 1]); colormap(getColorMap); ylabel('x-position [mm]'); xlabel('y-position [mm]'); axis image; % plot the simulated sensor data figure; imagesc(sensor_data, [-1, 1]); colormap(getColorMap); ylabel('Sensor Position'); xlabel('Time Step'); colorbar; title("Sensor data");