function eDVH(planName)

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

Ndvhbins = 1000;                                                            %number of dvh bins

prescTumor = open_presc('PTV70DosePlus.bin');                                %open prescription in Matlab
prescNormal = open_presc('NormalDosePlus.bin');
prescEyes = open_presc('EyesDosePlus.bin');

%dim = 1;                                                                    %2D
dim = 35;                                                                   %3D

fid = fopen(planName,'rb');                                                 %open plan in Matlab
plan = reshape(fread(fid,'float'),93,93,dim);
fclose(fid);

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

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

tumorMask = single(~~(full3D(prescTumor)));                                 %define tissue masks
normalMask = single(~~(full3D(prescNormal)));
eyesMask = single(~~(full3D(prescEyes)));

tumorDose = plan.*tumorMask;                                                %dose distributions in each ROI
normalDose = plan.*normalMask;
eyesDose = plan.*eyesMask;

tumorDoseSparse = sparse3D(tumorDose);                                      %convert 3D matrices to sparse matrices
normalDoseSparse = sparse3D(normalDose);
eyesDoseSparse = sparse3D(eyesDose);

tumorNormDose = ((tumorDoseSparse.non_zero_values)./(prescTumor.non_zero_values));  %calculate equivalent uniform dose
tumorAverageDose = mean(prescTumor.non_zero_values);
tumorEdose = tumorNormDose.*tumorAverageDose;

% NON UNIFORM PRESCRIPTIONS TO NORMAL TISSUE AND OAR

% normalNormDose = ((normalDoseSparse.non_zero_values)./(prescNormal.non_zero_values));  
% normalAverageDose = mean(normalDoseSparse.non_zero_values);
% normalEdose = normalNormDose.*normalAverageDose;
% 
% eyesNormDose = ((eyesDoseSparse.non_zero_values)./(prescEyes.non_zero_values));
% eyesAverageDose = mean(eyesDoseSparse.non_zero_values);
% eyesEdose = eyesNormDose.*eyesAverageDose;

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

dHistTumor = histc(tumorEdose,dvhbins);
% dHistNormal = histc(normalEdose,dvhbins);
% dHistEyes = histc(eyesEdose,dvhbins);

%dHistTumor = histc(tumorDoseSparse.non_zero_values,dvhbins);
dHistNormal = histc(normalDoseSparse.non_zero_values,dvhbins);
dHistEyes = histc(eyesDoseSparse.non_zero_values,dvhbins);

dHistTumorNorm = 100*dHistTumor./(double(tumorDoseSparse.Nind));
dHistNormalNorm = 100*dHistNormal./(double(normalDoseSparse.Nind));
dHistEyesNorm = 100*dHistEyes./(double(eyesDoseSparse.Nind));

DVHtumor = flipud(cumsum(flipud(dHistTumorNorm)));
DVHnormal = flipud(cumsum(flipud(dHistNormalNorm)));
DVHeyes = flipud(cumsum(flipud(dHistEyesNorm)));


createfigure(dvhbins,DVHtumor,DVHnormal,DVHeyes)

end