EIDORS: Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software

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GREIT Reconstruction for an adult human thorax geometry

Forward Model

fmdl= mk_library_model('adult_male_16el_lungs');
fmdl.electrode = fmdl.electrode([9:16,1:8]);
img = mk_image(fmdl, 1); % background conductivity
img.elem_data([fmdl.mat_idx{2};fmdl.mat_idx{3}]) = 0.3; % lungs
subplot(211); show_fem(img);
print_convert adult_ex01a.png
show_fem(img,[0,1]); view(2); %electrode #'s
print_convert adult_ex01b.png

Figure: Forward model used for training GREIT using contrasting lung regions

Training GREIT

[stim,msel] = mk_stim_patterns(16,1,[0,1],[0,1],{'no_meas_current'},1);
img.fwd_model.stimulation = stim;
img.fwd_model.normalize_measurements=1;
opt.imgsz = [32 32];
opt.distr = 3; % non-random, uniform
opt.Nsim = 500; % 500 hundred targets to train on, seems enough
opt.target_size = 0.03; %small targets
opt.target_offset = 0;
opt.noise_figure = .5; % this is key!
imdl=mk_GREIT_model(img, 0.25, [], opt);
imdl.fwd_model.meas_select = msel;

Show some images

Guardo R Boulay C Murray B Bertrand M An experimental study in electrical impedance tomography using backprojection reconstruction IEEE T Biomed Eng 38: 617−627, 1991

load montreal_data_1995
img= inv_solve(imdl, zc_resp(:,1), zc_resp);
img.calc_colours.ref_level=0;
show_slices(img);
print_convert adult_ex03b.png
img.elem_data= img.elem_data(:,22);
show_fem(img);
print_convert adult_ex03a.png

Figure: Forward model used for training GREIT using contrasting lung regions