WiscPlan_olderMV/opt/linlsqUtil/gradQVH.m

function gradQVH(uni,sig1,sig2,sig3,sig4,sig5,sig6,sig7,sig8)

addpath('C:\Documents and Settings\Steve\My Documents\Research\matlab')
addpath('C:\Documents and Settings\Steve\My Documents\Research\optNew\linlsqUtil')
addpath('C:\Documents and Settings\Steve\My Documents\Research\optNew\linlsqOpt\input')

Ndvhbins = 1000;                                                            %number of dvh bins

% prescTumorUni = open_presc('C:\Documents and Settings\Steve\My Documents\Research\Phantom\optResults\linGradStep1\phantrad1\boostrad2\contrast1\gradient2\input\G1DosePlus.bin');
% prescTumorSig1 = open_presc('C:\Documents and Settings\Steve\My Documents\Research\Phantom\optResults\linGradStep2\phantrad1\boostrad2\contrast1\gradient1\input\B1DosePlus.bin');                            %open prescription in Matlab
% prescTumorSig2 = open_presc('C:\Documents and Settings\Steve\My Documents\Research\Phantom\optResults\linGradStep5\phantrad1\boostrad2\contrast1\gradient1\input\B1DosePlus.bin');
% prescTumorSig3 = open_presc('C:\Documents and Settings\Steve\My Documents\Research\Phantom\optResults\linGradStep10\phantrad1\boostrad2\contrast1\gradient1\input\B1DosePlus.bin');
% prescTumorSig4 = open_presc('C:\Documents and Settings\Steve\My Documents\Research\Phantom\optResults\linGradContinuous\phantrad1\boostrad2\contrast1\gradient1\input\B1DosePlus.bin');
% prescTumorSig5 = open_presc('C:\Documents and Settings\Steve\My Documents\Research\Phantom\optResults\linGradStep2\phantrad1\boostrad2\contrast1\gradient1\input\G1DosePlus.bin');
% prescTumorSig6 = open_presc('C:\Documents and Settings\Steve\My Documents\Research\Phantom\optResults\linGradStep5\phantrad1\boostrad2\contrast1\gradient1\input\G1DosePlus.bin');
% prescTumorSig7 = open_presc('C:\Documents and Settings\Steve\My Documents\Research\Phantom\optResults\linGradStep10\phantrad1\boostrad2\contrast1\gradient1\input\G1DosePlus.bin');
prescTumorSig8 = open_presc('C:\Documents and Settings\Steve\My Documents\Research\Phantom\optResults\laplaceContinuous\phantrad0\boostrad0\contrast0\a4\input\TumorMinusBoostDosePlus.bin');

prescTumorUni = prescTumorSig8;
prescTumorSig1 = prescTumorSig8;
prescTumorSig2 = prescTumorSig8;
prescTumorSig3 = prescTumorSig8;
prescTumorSig4 = prescTumorSig8;
prescTumorSig5 = prescTumorSig8;
prescTumorSig6 = prescTumorSig8;
prescTumorSig7 = prescTumorSig8;

prescNormal = open_presc('C:\Documents and Settings\Steve\My Documents\Research\optNew\linlsqOpt\input\HN003uniPrescVolNew\NormalDosePlus.bin');
prescLarynx = open_presc('C:\Documents and Settings\Steve\My Documents\Research\optNew\linlsqOpt\input\HN003uniPrescVolNew\larynxDosePlus.bin');
prescRt = open_presc('C:\Documents and Settings\Steve\My Documents\Research\optNew\linlsqOpt\input\HN003uniPrescVolNew\RtparotidDosePlus.bin');
prescLt = open_presc('C:\Documents and Settings\Steve\My Documents\Research\optNew\linlsqOpt\input\HN003uniPrescVolNew\LtparotidDosePlus.bin');
prescCord = open_presc('C:\Documents and Settings\Steve\My Documents\Research\optNew\linlsqOpt\input\HN003uniPrescVolNew\CordDosePlus.bin');

dim1 = 170;
dim2 = dim1;
dim3 = 1;                                                                   %3D



fid = fopen(uni,'rb');                                           %open plans in Matlab
planUni = reshape(fread(fid,'float'),dim1,dim2,dim3);
fclose(fid);


fid = fopen(sig1,'rb');                                           %open plans in Matlab
planSig1 = reshape(fread(fid,'float'),dim1,dim2,dim3);
fclose(fid);

fid = fopen(sig2,'rb');                                           %open plans in Matlab
planSig2 = reshape(fread(fid,'float'),dim1,dim2,dim3);
fclose(fid);

fid = fopen(sig3,'rb');                                           %open plans in Matlab
planSig3 = reshape(fread(fid,'float'),dim1,dim2,dim3);
fclose(fid);

fid = fopen(sig4,'rb');                                           %open plans in Matlab
planSig4 = reshape(fread(fid,'float'),dim1,dim2,dim3);
fclose(fid);

fid = fopen(sig5,'rb');                                           %open plans in Matlab
planSig5 = reshape(fread(fid,'float'),dim1,dim2,dim3);
fclose(fid);

fid = fopen(sig6,'rb');                                           %open plans in Matlab
planSig6 = reshape(fread(fid,'float'),dim1,dim2,dim3);
fclose(fid);

fid = fopen(sig7,'rb');                                           %open plans in Matlab
planSig7 = reshape(fread(fid,'float'),dim1,dim2,dim3);
fclose(fid);

fid = fopen(sig8,'rb');                                           %open plans in Matlab
planSig8 = reshape(fread(fid,'float'),dim1,dim2,dim3);
fclose(fid);

for i=1:prescNormal.Nind;
    prescNormal.non_zero_values(i)=1;
end

for i=1:prescLarynx.Nind;
    prescLarynx.non_zero_values(i)=1;
end

for i=1:prescRt.Nind;
    prescRt.non_zero_values(i)=1;
end

for i=1:prescLt.Nind;
    prescLt.non_zero_values(i)=1;
end

for i=1:prescCord.Nind;
    prescCord.non_zero_values(i)=1;
end

tumorMaskUni = single(~~(full3D(prescTumorUni)));

tumorMaskSig1 = single(~~(full3D(prescTumorSig1)));                                 %define tissue masks
tumorMaskSig2 = single(~~(full3D(prescTumorSig2)));
tumorMaskSig3 = single(~~(full3D(prescTumorSig3)));
tumorMaskSig4 = single(~~(full3D(prescTumorSig4)));
tumorMaskSig5 = single(~~(full3D(prescTumorSig5)));
tumorMaskSig6 = single(~~(full3D(prescTumorSig6)));
tumorMaskSig7 = single(~~(full3D(prescTumorSig7)));
tumorMaskSig8 = single(~~(full3D(prescTumorSig8)));

larynxMask = single(~~(full3D(prescLarynx)));
rtMask = single(~~(full3D(prescRt)));
cordMask = single(~~(full3D(prescCord)));

tumorDoseUni = planUni.*tumorMaskUni;
tumorDoseSig1 = planSig1.*tumorMaskSig1;                                                %dose distributions in each ROI
tumorDoseSig2 = planSig2.*tumorMaskSig2;
tumorDoseSig3 = planSig3.*tumorMaskSig3;
tumorDoseSig4 = planSig4.*tumorMaskSig4;
tumorDoseSig5 = planSig5.*tumorMaskSig5;
tumorDoseSig6 = planSig6.*tumorMaskSig6;
tumorDoseSig7 = planSig7.*tumorMaskSig7;
tumorDoseSig8 = planSig8.*tumorMaskSig8;

tumorDoseSparseUni = sparse3D(tumorDoseUni);
tumorDoseSparseSig1 = sparse3D(tumorDoseSig1);
tumorDoseSparseSig2 = sparse3D(tumorDoseSig2);
tumorDoseSparseSig3 = sparse3D(tumorDoseSig3);
tumorDoseSparseSig4 = sparse3D(tumorDoseSig4);
tumorDoseSparseSig5 = sparse3D(tumorDoseSig5);
tumorDoseSparseSig6 = sparse3D(tumorDoseSig6);
tumorDoseSparseSig7 = sparse3D(tumorDoseSig7);
tumorDoseSparseSig8 = sparse3D(tumorDoseSig8);

tumorNormDoseUni = ((tumorDoseSparseUni.non_zero_values)./(prescTumorUni.non_zero_values));  %calculate equivalent uniform dose
tumorAverageDoseUni = mean(prescTumorUni.non_zero_values);
tumorEdoseUni = tumorNormDoseUni.*tumorAverageDoseUni;
tumorEdoseUni = tumorNormDoseUni;
indUni = find(((tumorNormDoseUni-1.).^2).^(1/2) >= 0.05);
volUni = 100.-double(length(indUni))./(double(tumorDoseSparseUni.Nind))*100

tumorNormDoseSig1 = ((tumorDoseSparseSig1.non_zero_values)./(prescTumorSig1.non_zero_values));  %calculate equivalent uniform dose
tumorAverageDoseSig1 = mean(prescTumorSig1.non_zero_values);
tumorEdoseSig1 = tumorNormDoseSig1.*tumorAverageDoseSig1;
tumorEdoseSig1 = tumorNormDoseSig1;
indSig1 = find(((tumorNormDoseSig1-1.).^2).^(1/2) >= 0.05);
volSig1 = 100.-double(length(indSig1))./(double(tumorDoseSparseSig1.Nind))*100

tumorNormDoseSig2 = ((tumorDoseSparseSig2.non_zero_values)./(prescTumorSig2.non_zero_values));  %calculate equivalent uniform dose
tumorAverageDoseSig2 = mean(prescTumorSig2.non_zero_values);
tumorEdoseSig2 = tumorNormDoseSig2.*tumorAverageDoseSig2;
tumorEdoseSig2 = tumorNormDoseSig2;
indSig2 = find(((tumorNormDoseSig2-1.).^2).^(1/2) >= 0.05);
volSig2 = 100.-double(length(indSig2))./(double(tumorDoseSparseSig2.Nind))*100

tumorNormDoseSig3 = ((tumorDoseSparseSig3.non_zero_values)./(prescTumorSig3.non_zero_values));  %calculate equivalent uniform dose
tumorAverageDoseSig3 = mean(prescTumorSig3.non_zero_values);
tumorEdoseSig3 = tumorNormDoseSig3.*tumorAverageDoseSig3;
tumorEdoseSig3 = tumorNormDoseSig3;
indSig3 = find(((tumorNormDoseSig3-1.).^2).^(1/2) >= 0.05);
volSig3 = 100.-double(length(indSig3))./(double(tumorDoseSparseSig3.Nind))*100

tumorNormDoseSig4 = ((tumorDoseSparseSig4.non_zero_values)./(prescTumorSig4.non_zero_values));  %calculate equivalent uniform dose
tumorAverageDoseSig4 = mean(prescTumorSig4.non_zero_values);
tumorEdoseSig4 = tumorNormDoseSig4.*tumorAverageDoseSig4;
tumorEdoseSig4 = tumorNormDoseSig4;
indSig4 = find(((tumorNormDoseSig4-1.).^2).^(1/2) >= 0.05);
volSig4 = 100.-double(length(indSig4))./(double(tumorDoseSparseSig4.Nind))*100

tumorNormDoseSig5 = ((tumorDoseSparseSig5.non_zero_values)./(prescTumorSig5.non_zero_values));  %calculate equivalent uniform dose
tumorAverageDoseSig5 = mean(prescTumorSig5.non_zero_values);
tumorEdoseSig5 = tumorNormDoseSig5.*tumorAverageDoseSig5;
tumorEdoseSig5 = tumorNormDoseSig5;
indSig5 = find(((tumorNormDoseSig5-1.).^2).^(1/2) >= 0.05);
volSig5 = 100.-double(length(indSig5))./(double(tumorDoseSparseSig5.Nind))*100

tumorNormDoseSig6 = ((tumorDoseSparseSig6.non_zero_values)./(prescTumorSig6.non_zero_values));  %calculate equivalent uniform dose
tumorAverageDoseSig6 = mean(prescTumorSig6.non_zero_values);
tumorEdoseSig6 = tumorNormDoseSig6.*tumorAverageDoseSig6;
tumorEdoseSig6 = tumorNormDoseSig6;
indSig6 = find(((tumorNormDoseSig6-1.).^2).^(1/2) >= 0.05);
volSig6 = 100.-double(length(indSig6))./(double(tumorDoseSparseSig6.Nind))*100

tumorNormDoseSig7 = ((tumorDoseSparseSig7.non_zero_values)./(prescTumorSig7.non_zero_values));  %calculate equivalent uniform dose
tumorAverageDoseSig7 = mean(prescTumorSig7.non_zero_values);
tumorEdoseSig7 = tumorNormDoseSig7.*tumorAverageDoseSig7;
tumorEdoseSig7 = tumorNormDoseSig7;
indSig7 = find(((tumorNormDoseSig7-1.).^2).^(1/2) >= 0.05);
volSig7 = 100.-double(length(indSig7))./(double(tumorDoseSparseSig7.Nind))*100

tumorNormDoseSig8 = ((tumorDoseSparseSig8.non_zero_values)./(prescTumorSig8.non_zero_values));  %calculate equivalent uniform dose
tumorAverageDoseSig8 = mean(prescTumorSig8.non_zero_values);
tumorEdoseSig8 = tumorNormDoseSig8.*tumorAverageDoseSig8;
tumorEdoseSig8 = tumorNormDoseSig8;
indSig8 = find(((tumorNormDoseSig8-1.).^2).^(1/2) >= 0.05);
volSig8 = 100.-double(length(indSig8))./(double(tumorDoseSparseSig8.Nind))*100



dMax = 1.1*max(tumorEdoseSig1);
dvhbins = [0:Ndvhbins-1]*dMax/Ndvhbins;

dHistTumorUni = histc(tumorEdoseUni,dvhbins);
dHistTumorSig1 = histc(tumorEdoseSig1,dvhbins);
dHistTumorSig2 = histc(tumorEdoseSig2,dvhbins);
dHistTumorSig3 = histc(tumorEdoseSig3,dvhbins);
dHistTumorSig4 = histc(tumorEdoseSig4,dvhbins);
dHistTumorSig5 = histc(tumorEdoseSig5,dvhbins);
dHistTumorSig6 = histc(tumorEdoseSig6,dvhbins);
dHistTumorSig7 = histc(tumorEdoseSig7,dvhbins);
dHistTumorSig8 = histc(tumorEdoseSig8,dvhbins);


dHistTumorNormUni = 100*dHistTumorUni./(double(tumorDoseSparseUni.Nind));
dHistTumorNormSig1 = 100*dHistTumorSig1./(double(tumorDoseSparseSig1.Nind));
dHistTumorNormSig2 = 100*dHistTumorSig2./(double(tumorDoseSparseSig2.Nind));
dHistTumorNormSig3 = 100*dHistTumorSig3./(double(tumorDoseSparseSig3.Nind));
dHistTumorNormSig4 = 100*dHistTumorSig4./(double(tumorDoseSparseSig4.Nind));
dHistTumorNormSig5 = 100*dHistTumorSig5./(double(tumorDoseSparseSig5.Nind));
dHistTumorNormSig6 = 100*dHistTumorSig6./(double(tumorDoseSparseSig6.Nind));
dHistTumorNormSig7 = 100*dHistTumorSig7./(double(tumorDoseSparseSig7.Nind));
dHistTumorNormSig8 = 100*dHistTumorSig8./(double(tumorDoseSparseSig8.Nind));


DVHtumorUni = flipud(cumsum(flipud(dHistTumorNormUni)));
DVHtumorSig1 = flipud(cumsum(flipud(dHistTumorNormSig1)));
DVHtumorSig2 = flipud(cumsum(flipud(dHistTumorNormSig2)));
DVHtumorSig3 = flipud(cumsum(flipud(dHistTumorNormSig3)));
DVHtumorSig4 = flipud(cumsum(flipud(dHistTumorNormSig4)));
DVHtumorSig5 = flipud(cumsum(flipud(dHistTumorNormSig5)));
DVHtumorSig6 = flipud(cumsum(flipud(dHistTumorNormSig6)));
DVHtumorSig7 = flipud(cumsum(flipud(dHistTumorNormSig7)));
DVHtumorSig8 = flipud(cumsum(flipud(dHistTumorNormSig8)));



% tumorSigFigure(dvhbins,DVHtumorUni,DVHtumorSig1,DVHtumorSig2,DVHtumorSig3,DVHtumorSig4,DVHtumorSig5,DVHtumorSig6,DVHtumorSig7,DVHtumorSig8)

end