A QUICK START DEMO - simulations, demodulation, beamforming, compounding

In this quick'n easy tutorial, it is shown how to simulate an ultrasound image from the transmit of plane waves. A few scatterers will be insonified with steered planes waves to obtain a compound image. You will use the following fundamental steps:

  1. A transducer will be chosen with GETPARAM,
  2. Transmit delays will be designed with TXDELAY
  3. A pressure field will be calculated with PFIELD
  4. RF signals will be simulated with the function SIMUS.
  5. The RF signals will be I/Q demodulated with RF2IQ,
  6. then beamformed with DAS.
  7. A compound image will eventually be generated.

Contents

Scatterers

Define a few scatterers ...

xs = [1.7 1.3 0.7 0 -0.7 -1.3 -1.7 0 -1 1]*1e-2; % in m
zs = [2.8 3.2 3.5 3.6 3.5 3.2 2.8 2 0.8 0.8]*1e-2; % in m

... with their reflection coefficients

RC = ones(size(xs));

Select a transducer with GETPARAM

We want a 128-element linear array.

param = getparam('L11-5v');

The structure param contains the tranducer properties.

Design the transmit delays with TXDELAY

The scatterers will be insonified with 21 plane waves steered at -10 to +10 degrees.

tilt = linspace(-10,10,21)/180*pi; % tilt angles in rad
txdel = cell(21,1); % this cell will contain the transmit delays

Use TXDELAY to calculate the transmit delays for the 21 plane waves.

for k = 1:21
    txdel{k} = txdelay(param,tilt(k));
end

Check a pressure field with PFIELD

Let us visualize the 5th pressure field.

Define a 100 $\times$ 100 8-cm-by-8-cm grid.

[xi,zi] = meshgrid(linspace(-4e-2,4e-2,100),linspace(0,8e-2,100));

Simulate the pressure field.

P = pfield(xi,zi,txdel{5},param);

Display the 5th pressure field.

imagesc(xi(1,:)*1e2,zi(:,1)*1e2,20*log10(P/max(P(:))))
caxis([-30 0]) % dynamic range = [-30,0] dB
c = colorbar;
c.YTickLabel{end} = '0 dB';
colormap([1-hot; hot])
set(gca,'XColor','none','box','off')
axis equal ij
ylabel('[cm]')
title('The 5^{th} plane wave - RMS pressure field')

Simulate RF signals with SIMUS

We will now simulate 21 series of RF signals. Each series will contain 128 RF signals, as the simulated linear array contains 128 elements.

RF = cell(17,1); % this cell will contain the RF series
param.fs = 4*param.fc; % sampling frequency in Hz

option.WaitBar = false; % remove the progress bar of SIMUS
for k = 1:21
    RF{k} = simus(xs,zs,RC,txdel{k},param,option);
end

This is the 64th RF signal of the 1st series:

rf = RF{1}(:,64);
t = (0:numel(rf)-1)/param.fs*1e6; % time (ms)
plot(t,rf)
set(gca,'YColor','none','box','off')
xlabel('time (\mus)')
title('RF signal of the 64^{th} element (1^{st} series, tilt = -20{\circ})')
axis tight

Demodulate the RF signals with RF2IQ

Before beamforming, the RF signals must be I/Q demodulated.

IQ = cell(21,1);  % this cell will contain the I/Q series

for k = 1:21
    IQ{k} = rf2iq(RF{k},param.fs,param.fc);
end

This is the 64th I/Q signal of the 1st series:

iq = IQ{1}(:,64);
plot(t,real(iq),t,imag(iq))
set(gca,'YColor','none','box','off')
xlabel('time (\mus)')
title('I/Q signal of the 64^{th} element (1^{st} series, tilt = -10{\circ})')
legend({'in-phase','quadrature'})
axis tight

Beamform the I/Q signals with DAS

It is recommended to use an adequate receive f-number when beamforming. Define a void f-number; it will be determined automatically by DAS from the element directivity.

param.fnumber = [];

Define a 200 $\times$ 200 4-cm-by-4-cm image grid.

[xi,zi] = meshgrid(linspace(-2e-2,2e-2,200),linspace(0,4e-2,200));

Beamform the I/Q signals using a delay-and-sum with the function DAS.

bIQ = zeros(200,200,21);  % this array will contain the 21 I/Q images

h = waitbar(0,'');
for k = 1:21
    waitbar(k/21,h,['DAS: I/Q series #' int2str(k) ' of 21'])
    bIQ(:,:,k) = das(IQ{k},xi,zi,txdel{k},param);
end
close(h)

Compound ultrasound image

An ultrasound image is obtained by log-compressing the amplitude of the beamformed I/Q signals. Have a look at the images obtained when steering at -10 degrees.

I = bmode(bIQ(:,:,1),40); % log-compressed image
imagesc(xi(1,:)*1e2,zi(:,1)*1e2,I)
colormap gray
title('PW-based echo image with a tilt angle of -10{\circ}')

axis equal ij
set(gca,'XColor','none','box','off')
c = colorbar;
c.YTick = [0 255];
c.YTickLabel = {'-40 dB','0 dB'};
ylabel('[cm]')

The individual images are of poor quality. Generate a compound image with the series of 21 diverging waves steered at different angles.

cIQ = sum(bIQ,3); % this is the compound beamformed I/Q
I = bmode(cIQ,40); % log-compressed image
imagesc(xi(1,:)*1e2,zi(:,1)*1e2,I)
colormap gray
title('Compound PW-based echo image')

axis equal ij
set(gca,'XColor','none','box','off')
c = colorbar;
c.YTick = [0 255];
c.YTickLabel = {'-40 dB','0 dB'};
ylabel('[cm]')



See also

simus, rf2iq, das

Another demonstration to know more about SIMUS: Diverging-wave echocardiography



About the author

Damien Garcia, Eng., Ph.D.
INSERM researcher
Creatis, University of Lyon, France

websites: BioméCardio, MUST



Date modified


Published with MATLAB® R2020a