EIDORS: Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software

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EIDORS image reconstructions

EIDORS data structures: the inv_model

% Basic Image reconstruction
% $Id: tutorial110a.m 1535 2008-07-26 15:36:27Z aadler $

% Load some data
load iirc_data_2006

% grey background
calc_colours('greylev',-.1);

% Get a 2D image reconstruction model
imdl= mk_common_model('c2c');
% Set stimulation patterns. Use meas_current
% Stimulation of [1,0] (not [0,1]) is needed for this device (IIRC)
imdl.fwd_model.stimulation = mk_stim_patterns(16,1,[1,0],[0,1],{'meas_current'},1);
% Remove meas_select field because all 16x16 patterns are used
imdl.fwd_model = rmfield( imdl.fwd_model, 'meas_select');


vi= real(v_rotate(:,9))/1e4; vh= real(v_reference)/1e4;

for idx= 1:3
   if     idx==1
      imdl.hyperparameter.value= 1e-3;
   elseif idx==2
      imdl.hyperparameter.value= 3e-3;
   elseif idx==3
      imdl.hyperparameter.value= 1e-2;
   end
   img= inv_solve(imdl, vh, vi);

   subplot(2,3,idx);
   show_slices(img);

   subplot(2,3,idx+3);
   z=calc_slices(img);
   c=calc_colours(z);
   h=mesh(z,c); view(-11,44);
   set(h,'CDataMapping','Direct');
   set(gca,{'XLim','YLim','ZLim','XTickLabel','YTickLabel'}, ...
        {[1 64],[1 64],[-3.3,0.5],[],[]})
end

print -r100 -dpng tutorial110a.png;

Figure: Image reconstructions shown as images (top) or meshes (bottom) for different hyperparameter values.