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matRad_objFunc.m
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matRad_objFunc.m
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function [f, g] = matRad_objFunc(w,dij,cst)
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% matRad objective function for inverse planning supporting mean dose
% objectives, EUD objectives, squared overdosage, squared underdosage, and
% squared deviation
%
% call
% [f, g] = matRad_objFunc(w,dij,cst)
%
% input
% w: bixel weight vector
% dij: dose influence matrix
% cst: matRad cst struct
%
% output
% f: objective function value
% g: gradient
%
% References
% [1] http://www.sciencedirect.com/science/article/pii/S0958394701000577
% [2] http://www.sciencedirect.com/science/article/pii/S0360301601025858
%
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Copyright 2015, Mark Bangert, on behalf of the matRad development team
%
%
% This file is part of matRad.
%
% matrad is free software: you can redistribute it and/or modify it under
% the terms of the GNU General Public License as published by the Free
% Software Foundation, either version 3 of the License, or (at your option)
% any later version.
%
% matRad is distributed in the hope that it will be useful, but WITHOUT ANY
% WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
% FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
% details.
%
% You should have received a copy of the GNU General Public License in the
% file license.txt along with matRad. If not, see
% <http://www.gnu.org/licenses/>.
%
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Calculate dose
d = dij.physicalDose*w;
% Numbers of voxels
numVoxels = size(dij.physicalDose,1);
% Initializes f
f = 0;
% Initializes delta
delta_underdose = zeros(numVoxels,1);
delta_overdose = zeros(numVoxels,1);
delta_deviation = zeros(numVoxels,1);
delta_mean = zeros(numVoxels,1);
delta_EUD = zeros(numVoxels,1);
% compute objective function for every VOI.
for i = 1:size(cst,1)
% Only take OAR or target VOI.
if ~isempty(cst{i,4}) && ( isequal(cst{i,3},'OAR') || isequal(cst{i,3},'TARGET') )
% get dose vector in current VOI
d_i = d(cst{i,4});
% loop over the number of constraints for the current VOI
for j = 1:size(cst{i,6},1)
% get Penalty
rho = cst{i,6}(j).parameter(1);
if isequal(cst{i,6}(j).type, 'square underdosing')
if ~isequal(cst{i,3},'OAR')
% underdose : Dose minus prefered dose
underdose = d_i - cst{i,6}(j).parameter(2);
% apply positive operator
underdose(underdose>0) = 0;
% calculate objective function
f = f + (rho/size(cst{i,4},1))*(underdose'*underdose);
% calculate delta
delta_underdose(cst{i,4}) = delta_underdose(cst{i,4}) +...
(rho/size(cst{i,4},1))*underdose;
else
disp(['square underdosing constraint for ' cst{i,2} ' will be skipped'])
end
elseif isequal(cst{i,6}(j).type, 'square overdosing')
% overdose : Dose minus prefered dose
overdose = d_i - cst{i,6}(j).parameter(2);
% apply positive operator
overdose(overdose<0) = 0;
% calculate objective function
f = f + (rho/size(cst{i,4},1))*(overdose'*overdose);
%calculate delta
delta_overdose(cst{i,4}) = delta_overdose(cst{i,4}) + ...
(rho/size(cst{i,4},1))*overdose;
elseif isequal(cst{i,6}(j).type, 'square deviation')
if ~isequal(cst{i,3},'OAR')
% deviation : Dose minus prefered dose
deviation = d_i - cst{i,6}(j).parameter(2);
% claculate objective function
f = f + (rho/size(cst{i,4},1))*(deviation'*deviation);
% calculate delta
delta_deviation(cst{i,4}) = delta_deviation(cst{i,4}) +...
(rho/size(cst{i,4},1))*deviation;
else
disp(['square deviation constraint for ' cst{i,2} ' will be skipped'])
end
elseif isequal(cst{i,6}(j).type, 'mean')
if ~isequal(cst{i,3},'TARGET')
% calculate objective function
f = f + (rho/size(cst{i,4},1))*sum(d_i);
% calculate delta
delta_mean(cst{i,4}) = delta_mean(cst{i,4}) + ...
(rho/size(cst{i,4},1))*ones(size(cst{i,4},1),1);
else
disp(['mean constraint for ' cst{i,2} ' will be skipped'])
end
elseif isequal(cst{i,6}(j).type, 'EUD')
if ~isequal(cst{i,3},'TARGET')
% get exponent for EUD
exponent = cst{i,6}(j).parameter(2);
% calculate objective function and delta
if sum(d_i.^exponent)>0
f = f + rho*nthroot((1/size(cst{i,4},1))*sum(d_i.^exponent),exponent);
delta_EUD(cst{i,4}) = delta_EUD(cst{i,4}) + ...
rho*nthroot(1/size(cst{i,4},1),exponent) * sum(d_i.^exponent)^((1-exponent)/exponent) * (d_i.^(exponent-1));
end
if sum(~isfinite(delta_EUD)) > 0 % check for inf and nan for numerical stability
error(['EUD computation for ' cst{i,2} ' failed. Reduce exponent to resolve numerical problems.']);
end
else
disp(['EUD constraint for ' cst{i,2} ' will be skipped'])
end
else
error('undefined objective in cst struct');
end
end
end
end
if nargout > 1
% Calculate gradient
g = (( 2*(delta_underdose + delta_overdose + delta_deviation) + delta_mean + delta_EUD )' * dij.physicalDose)';
end
end