k-Wave User Forum » Topic: Why can't I change the frequency to 40MHz

k-Wave User Forum » Topic: Why can't I change the frequency to 40MHz http://www.k-wave.org/forum/topic/why-cant-i-change-the-frequency-to-40mhz Support for the k-Wave MATLAB toolbox en-US Tue, 12 May 2026 23:07:57 +0000 http://bbpress.org/?v=1.0.2 <![CDATA[Search]]> q http://www.k-wave.org/forum/search.php yuanbo on "Why can't I change the frequency to 40MHz" http://www.k-wave.org/forum/topic/why-cant-i-change-the-frequency-to-40mhz#post-8860 Tue, 18 Jul 2023 07:24:50 +0000 yuanbo 8860@http://www.k-wave.org/forum/ % Defining An Ultrasound Transducer Example % % In principle, simulations using diagnostic ultrasound transducers can be % run following the examples given under Time Varying Source Problems. % However, assigning the grid points that belong to each transducer % element, and then assigning the correctly delayed input signals to each % point of each element can be a laborious task. For this purpose, a % special input object created using the kWaveTransducer class can be % substituted for either the source or sensor inputs (or both). This % example illustrates how this object is created and can be used to % simulate the field produced by an ultrasound transducer. % % Note, transducer inputs can only be used in 3D simulations and thus these % examples are inherently memory and CPU intensive. Whilst the grid sizes % and source frequencies used in the examples have been scaled down for the % purpose of demonstrating the capabilities of the toolbox (the inputs do % not necessarily represent realistic ultrasound settings), they still % require a comparatively large amount of computational resources. To % reduce this load, it is advised to run the simulations in single % precision by setting the optional input 'DataCast' to 'single'. % Similarly, if you have access to a recent model GPU and the MATLAB % Parallel Computing Toolbox R2012a or later, the simulation times can be % significantly reduced by setting 'DataCast' to 'gpuArray-single'. % Alternatively, the simulations can be run using the optimised C++ code. % See the k-Wave Manual for more information. % % The creation of a kWaveTransducer object will only work in versions of % MATLAB recent enough to support user defined classes. % % author: Bradley Treeby % date: 20th July 2011 % last update: 11th June 2017 % % This function is part of the k-Wave Toolbox (<a href="http://www.k-wave.org" rel="nofollow">http://www.k-wave.org</a>) % Copyright (C) 2011-2017 Bradley Treeby % This file is part of k-Wave. k-Wave is free software: you can % redistribute it and/or modify it under the terms of the GNU Lesser % General Public License as published by the Free Software Foundation, % either version 3 of the License, or (at your option) any later version. % % k-Wave is distributed in the hope that it will be useful, but WITHOUT ANY % WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS % FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for % more details. % % You should have received a copy of the GNU Lesser General Public License % along with k-Wave. If not, see <http://www.gnu.org/licenses/>. clearvars; % simulation settings DATA_CAST = 'single'; % ========================================================================= % DEFINE THE K-WAVE GRID % ========================================================================= % set the size of the perfectly matched layer (PML) PML_X_SIZE = 20; % [grid points] PML_Y_SIZE = 10; % [grid points] PML_Z_SIZE = 10; % [grid points] % set total number of grid points not including the PML Nx = 128 - 2*PML_X_SIZE; % [grid points] Ny = 128 - 2*PML_Y_SIZE; % [grid points] Nz = 64 - 2*PML_Z_SIZE; % [grid points] % set desired grid size in the x-direction not including the PML x = 40e-3; % [m] % calculate the spacing between the grid points dx = x/Nx; % [m] dy = dx; % [m] dz = dx; % [m] % create the k-space grid kgrid = kWaveGrid(Nx, dx, Ny, dy, Nz, dz); % ========================================================================= % DEFINE THE MEDIUM PARAMETERS % ========================================================================= % define the properties of the propagation medium medium.sound_speed = 1540; % [m/s] medium.density = 1000; % [kg/m^3] medium.alpha_coeff = 0.75; % [dB/(MHz^y cm)] medium.alpha_power = 2; medium.BonA = 6; % create the time array t_end = 40e-6; % [s] kgrid.makeTime(medium.sound_speed, [], t_end); % ========================================================================= % DEFINE THE INPUT SIGNAL % ========================================================================= % define properties of the input signal source_strength = 1e6; % [Pa] tone_burst_freq = 40e6; % [Hz] tone_burst_cycles = 1; % create the input signal using toneBurst input_signal = toneBurst(1/kgrid.dt, tone_burst_freq, tone_burst_cycles); % scale the source magnitude by the source_strength divided by the % impedance (the source is assigned to the particle velocity) input_signal = (source_strength ./ (medium.sound_speed * medium.density)) .* input_signal; % ========================================================================= % DEFINE THE ULTRASOUND TRANSDUCER % ========================================================================= % physical properties of the transducer transducer.number_elements = 72; % total number of transducer elements transducer.element_width = 1; % width of each element [grid points] transducer.element_length = 12; % length of each element [grid points] transducer.element_spacing = 0; % spacing (kerf width) between the elements [grid points] transducer.radius = inf; % radius of curvature of the transducer [m] % calculate the width of the transducer in grid points transducer_width = transducer.number_elements * transducer.element_width ... + (transducer.number_elements - 1) * transducer.element_spacing; % use this to position the transducer in the middle of the computational grid transducer.position = round([1, Ny/2 - transducer_width/2, Nz/2 - transducer.element_length/2]); % properties used to derive the beamforming delays transducer.sound_speed = 1540; % sound speed [m/s] transducer.focus_distance = 20e-3; % focus distance [m] transducer.elevation_focus_distance = 19e-3; % focus distance in the elevation plane [m] transducer.steering_angle = 0; % steering angle [degrees] % apodization transducer.transmit_apodization = 'Rectangular'; transducer.receive_apodization = 'Rectangular'; % define the transducer elements that are currently active transducer.active_elements = zeros(transducer.number_elements, 1); transducer.active_elements(21:52) = 1; % append input signal used to drive the transducer transducer.input_signal = input_signal; % create the transducer using the defined settings transducer = kWaveTransducer(kgrid, transducer); % print out transducer properties transducer.properties; % ========================================================================= % DEFINE SENSOR MASK % ========================================================================= % create a binary sensor mask with four detection positions sensor.mask = zeros(Nx, Ny, Nz); sensor.mask([Nx/4, Nx/2, 3*Nx/4], Ny/2, Nz/2) = 1; % ========================================================================= % RUN THE SIMULATION % ========================================================================= % set the input settings input_args = {'DisplayMask', transducer.all_elements_mask | sensor.mask, ... 'PMLInside', false, 'PlotPML', false, 'PMLSize', [PML_X_SIZE, PML_Y_SIZE, PML_Z_SIZE], ... 'DataCast', DATA_CAST, 'PlotScale', [-1/2, 1/2] * source_strength}; % run the simulation [sensor_data] = kspaceFirstOrder3D(kgrid, medium, transducer, sensor, input_args{:}); % calculate the amplitude spectrum of the input signal and the signal % recorded each of the sensor positions [f_input, as_input] = spect([input_signal, zeros(1, 2 * length(input_signal))], 1/kgrid.dt); [~, as_1] = spect(sensor_data(1, :), 1/kgrid.dt); [~, as_2] = spect(sensor_data(2, :), 1/kgrid.dt); [f, as_3] = spect(sensor_data(3, :), 1/kgrid.dt); % ========================================================================= % VISUALISATION % ========================================================================= % plot the input signal and its frequency spectrum figure; subplot(2, 1, 1); plot((0:kgrid.dt:(length(input_signal) - 1) * kgrid.dt) * 1e6, input_signal, 'k-'); xlabel('Time [\mus]'); ylabel('Particle Velocity [m/s]'); subplot(2, 1, 2); plot(f_input .* 1e-6, as_input./max(as_input(:)), 'k-'); hold on; line([tone_burst_freq, tone_burst_freq] .* 1e-6, [0 1], 'Color', 'k', 'LineStyle', '--'); xlabel('Frequency [MHz]'); ylabel('Amplitude Spectrum [au]'); f_max = medium.sound_speed / (2 * dx); set(gca, 'XLim', [0, f_max .* 1e-6]); % plot the recorded time series figure; stackedPlot(kgrid.t_array * 1e6, {'Sensor Position 1', 'Sensor Position 2', 'Sensor Position 3'}, sensor_data); xlabel('Time [\mus]'); % plot the corresponding amplitude spectrums figure; plot(f .* 1e-6, as_1 ./ max(as_1(:)), 'k-', ... f .* 1e-6, as_2 ./ max(as_1(:)), 'b-', ... f .* 1e-6, as_3 ./ max(as_1(:)), 'r-'); legend('Sensor Position 1', 'Sensor Position 2', 'Sensor Position 3'); xlabel('Frequency [MHz]'); ylabel('Normalised Amplitude Spectrum [au]'); f_max = medium.sound_speed / (2 * dx); set(gca, 'XLim', [0, f_max .* 1e-6]);