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%--------------------------------------------------------------------------
% This file is part of the ASTRA Toolbox
%
% Copyright: 2010-2022, imec Vision Lab, University of Antwerp
% 2014-2022, CWI, Amsterdam
% License: Open Source under GPLv3
% Contact: astra@astra-toolbox.com
% Website: http://www.astra-toolbox.com/
%--------------------------------------------------------------------------
classdef DARToptimizerBoneStudy < handle
%----------------------------------------------------------------------
properties (SetAccess=public,GetAccess=public)
% optimization options
max_evals = 100;
tolerance = 0.1;
display = 'off';
% DART options
DART_iterations = 50;
D_base = [];
end
%----------------------------------------------------------------------
properties (SetAccess=private,GetAccess=public)
stats = struct();
end
%----------------------------------------------------------------------
methods (Access=public)
%------------------------------------------------------------------
% Constructor
function this = DARToptimizerBoneStudy(D_base)
this.D_base = D_base;
this.stats.params = {};
this.stats.values = [];
this.stats.rmse = [];
this.stats.f_250 = [];
this.stats.f_100 = [];
this.stats.w_250 = [];
this.stats.w_125 = [];
end
%------------------------------------------------------------------
function opt_values = run(this, params, initial_values)
if nargin < 3
for i = 1:numel(params)
initial_values(i) = eval(['this.D_base.' params{i} ';']);
end
end
% fminsearch
options = optimset('display', this.display, 'MaxFunEvals', this.max_evals, 'TolX', this.tolerance);
opt_values = fminsearch(@optim_func, initial_values, options, this.D_base, params, this);
% save to D_base
for i = 1:numel(params)
eval(sprintf('this.D_base.%s = %d;',params{i}, opt_values(i)));
end
end
%------------------------------------------------------------------
end
end
%--------------------------------------------------------------------------
function rmse = optim_func(values, D_base, params, Optim)
% copy DART
D = D_base.deepcopy();
% set parameters
for i = 1:numel(params)
eval(sprintf('D.%s = %d;',params{i}, values(i)));
D.output.pre = [D.output.pre num2str(values(i)) '_'];
end
% evaluate
if D.initialized == 0
D.initialize();
end
rng('default');
D.iterate(Optim.DART_iterations);
% compute rmse
ROI = load('roi.mat');
[rmse, f_250, f_100, w_250, w_125] = compute_rmse(D.S, ROI);
%projection = D.tomography.project(D.S);
%proj_diff = sum((projection(:) - D.base.sinogram(:)).^2);
% save
Optim.stats.params{end+1} = params;
Optim.stats.values(end+1,:) = values;
Optim.stats.rmse(end+1) = rmse;
Optim.stats.f_250(end+1) = f_250;
Optim.stats.f_100(end+1) = f_100;
Optim.stats.w_250(end+1) = w_250;
Optim.stats.w_125(end+1) = w_125;
disp([num2str(values) ': ' num2str(rmse)]);
end
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