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EIDORS: Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software

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GREIT Reconstruction for an neonate human thorax geometry

Data

Data are available Here. Data were recorded from a 10-day old spontaneously breathing neonate lying in the prone position with the head turned to the left, as documented in: S. Heinrich, H. Schiffmann, A. Frerichs, A. Klockgether-Radke, I. Frerichs, Body and head position effects on regional lung ventilation in infants: an electrical impedance tomography study. Intensive Care Med., 32:1392-1398, 2006.

Subject Image:

Use Circular GREIT v1.0 model

Reconstruction model

% Inverse model
imdl = mk_common_gridmdl('GREITc1');

% Data: eidors3d.sf.net/data_contrib/if-neonate-spontaneous/if-neonate-spontaneous.zip
vv= eidors_readdata('P04P-1016.get');

Reconstruct images

vh = mean(vv,2);        % reference is average
vi = vv(:,[45,70,173]); %3 inspirations

img = inv_solve(imdl,vh,vi);

img.show_slices.img_cols = 3;
img.show_slices.sep      = 2;
img.calc_colours.ref_level=0;
show_slices(img);

print_convert neonate_ex02a.png

Figure: Images of three different breaths (end inspiration) Reconstruct temporal signals

vh = mean(vv,2);        % reference is average
img = inv_solve(imdl,vh,vv);
img.calc_colours.ref_level=0;
img.calc_colours.npoints  =32;

% Yposns of where to plot
yposns = [10:5:25];

% Show image
clf; axes('position',[0.05,0.5,0.25,0.45]);
img1= img; img1.elem_data = img.elem_data(:,45);
show_slices(img1);
hold on;
plot(10,yposns,'s','LineWidth',5);
hold off;

% Show plots
imgs = calc_slices(img);
axes('position',[0.30,0.6,0.65,0.25]);

imgs = permute(imgs,[3,1,2]);
taxis =  (0:size(imgs,1)-1)/13; % frame rate = 13
plot(taxis,imgs(:,yposns,10),'LineWidth',2);
axis tight

print_convert neonate_ex03a.png

Figure: (bottom) time course of several lung pixels

Use Elliptic GREIT model

The shape of a neonate is roughly elliptical. Based on the neonate CT here, the elliptical ration is about 1:1.14.

n_elecs = 16;

% Elliptic model
[fmdle,midx] = ng_mk_ellip_models([1, 1.14,1,0.15] ,[n_elecs,0.5],[0.05]);
[stim,msel] =  mk_stim_patterns(n_elecs,1,[0,1],[0,1],{'no_meas_current'}, 1);
fmdle.stimulation =  stim;       
fmdle.meas_select =  msel;       
fmdle.normalize_measurements = 1;

% GREIT Ellip - circ objects
opt.distr = 0; % central
opt.noise_figure = 0.5;
imdl = mk_GREIT_model(mk_image(fmdle,1), 0.25, [], opt);

vh = mean(vv,2);        % reference is average
vi = vv(:,[45,70,173]); %3 inspirations

img = inv_solve(imdl,vh,vi);

img.show_slices.img_cols = 3;
img.show_slices.sep      = 2;
img.calc_colours.ref_level=0;
show_slices(img);

print_convert neonate_ex04a.png

Figure: Images of lungs using ellipcal GREIT reconstruction

Last Modified: $Date: 2011-07-15 06:48:46 -0400 (Fri, 15 Jul 2011) $ by $Author: aadler $