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prepNMS.m
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prepNMS.m
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%% ---- Prepare new manual masks ---- %%
% This function is to prepare new manual masks we are going to use in the
% study "The Reproducibility of deep learning-based segmentation of the
% prostate on T2-weighted MR images".
%
% Sunoqrot, M.R.S.; Selnæs, K.M.; Sandsmark, E.; Langørgen, S.; Bertilsson,
% H.; Bathen, T.F.; Elschot, M. The Reproducibility of Deep Learning-Based
% Segmentation of the Prostate Gland and Zones on T2-Weighted MR Images.
% Diagnostics 2021, 11, 1690. https://doi.org/10.3390/diagnostics11091690
% https://www.mdpi.com/2075-4418/11/9/1690
%
% By Mohammed R. S. Sunoqrot, MR cancer group, NTNU, Trondheim, Norway
% 05.Oct.2020
%
% Input:
% 1. masterPath: The path to the master analysis file. (string)
%
function prepNMS(masterPath)
%% Paths
paths.train.main = fullfile(masterPath,'Data','Train','Segmentation','Manual');
paths.train.original = fullfile(paths.train.main,'Original');
paths.train.adjusted = fullfile(paths.train.main,'Adjusted');
paths.test.main = fullfile(masterPath,'Data','Segmentation','Manual');
paths.test.original.Scan1 = fullfile(paths.test.main,'Original','Scan1');
paths.test.original.Scan2 = fullfile(paths.test.main,'Original','Scan2');
paths.test.adjusted.Scan1 = fullfile(paths.test.main,'Adjusted','Scan1');
paths.test.adjusted.Scan2 = fullfile(paths.test.main,'Adjusted','Scan2');
paths.clinical = fullfile(masterPath,'SheetTableAll.mat');
paths.allVois = fullfile(masterPath,'vois');
%% Load
load(paths.clinical)
%% Options
options = {'Train','Scan1','Scan2'};
%% Generate new masks
% Loop over the options
for ii = 1:numel(options)
% Get the folder paths for original and ajusted cases
if ii == 1
tpo = paths.train.original;
tpa = paths.train.adjusted;
tpWP = fullfile(paths.train.main,'Final','WP');
tpPZ = fullfile(paths.train.main,'Final','PZ');
tpTZ = fullfile(paths.train.main,'Final','TZ');
tpWPh = fullfile(paths.train.main,'Final','WPh');
tpPZh = fullfile(paths.train.main,'Final','PZh');
tpTZh = fullfile(paths.train.main,'Final','TZh');
tpWPl = fullfile(paths.train.main,'Final','WPl');
tpPZl = fullfile(paths.train.main,'Final','PZl');
tpTZl = fullfile(paths.train.main,'Final','TZl');
tpPZTZ = fullfile(paths.train.main,'Final','PZTZ');
if ~exist(tpWP,'dir')
mkdir(tpWP)
mkdir(tpPZ)
mkdir(tpTZ)
mkdir(tpWPh)
mkdir(tpPZh)
mkdir(tpTZh)
mkdir(tpWPl)
mkdir(tpPZl)
mkdir(tpTZl)
mkdir(tpPZTZ)
end
else
tpo = paths.test.original.(options{ii});
tpa = paths.test.adjusted.(options{ii});
tpWP = fullfile(paths.test.main,'Final',options{ii},'WP');
tpPZ = fullfile(paths.test.main,'Final',options{ii},'PZ');
tpTZ = fullfile(paths.test.main,'Final',options{ii},'TZ');
tpWPh = fullfile(paths.test.main,'Final',options{ii},'WPh');
tpPZh = fullfile(paths.test.main,'Final',options{ii},'PZh');
tpTZh = fullfile(paths.test.main,'Final',options{ii},'TZh');
tpWPl = fullfile(paths.test.main,'Final',options{ii},'WPl');
tpPZl = fullfile(paths.test.main,'Final',options{ii},'PZl');
tpTZl = fullfile(paths.test.main,'Final',options{ii},'TZl');
tpPZTZ = fullfile(paths.test.main,'Final',options{ii},'PZTZ');
if ~exist(tpWP,'dir')
mkdir(tpWP)
mkdir(tpPZ)
mkdir(tpTZ)
mkdir(tpWPh)
mkdir(tpPZh)
mkdir(tpTZh)
mkdir(tpWPl)
mkdir(tpPZl)
mkdir(tpTZl)
mkdir(tpPZTZ)
end
end
% List the avilable cases in the folder
dtpo = dir(fullfile(tpo,'*.mhd'));
dtpa = dir(fullfile(tpa,'*.mhd'));
% Loop over the cases inside the adjusted cases folder
for jj = 1:numel(dtpa)
% Display the current case name
disp([options{ii} ' -> ' dtpa(jj).name(1:18)])
% Current case
FilenameO = fullfile(dtpo(jj).folder,dtpa(jj).name);
FilenameA = fullfile(dtpa(jj).folder,dtpa(jj).name);
currentCase = dtpa(jj).name(1:18);
currentCaseIdx = find(contains(SheetTableAll.Sheet_ID,currentCase));
% Read the MetaIO in matlab
[StrDataxO, ~, ~] = elxMetaIOFileToStrDatax(FilenameO, 0);
[StrDataxA, ~, ~] = elxMetaIOFileToStrDatax(FilenameA, 0);
im3dO = elxStrDataxToIm3d(StrDataxO);
im3dA = elxStrDataxToIm3d(StrDataxA);
% Lesions index
lesionsIdx = im3dO.Data>2;
lesion1Idx = im3dO.Data==3;
lesion2Idx = im3dO.Data==4;
lesion3Idx = im3dO.Data==5;
%% 1. Whole prostate mask including the lesions
Prostate = im3dA;
Prostate.Data = Prostate.Data>0;
%% 2. Whole prostate mask excluding the lesions
HealthyProstate = Prostate;
HealthyProstate.Data(lesionsIdx) = 0;
%% 3. TZ mask including the lesions
TZ = im3dA;
TZ.Data = TZ.Data==2;
%% 4. TZ mask excluding the lesions
TZHealthy = TZ;
TZHealthy.Data(lesionsIdx) = 0;
%% 5. PZ mask including the lesions
PZ = im3dA;
PZ.Data = PZ.Data==1;
%% 6. TZ mask excluding the lesions
PZHealthy = PZ;
PZHealthy.Data(lesionsIdx) = 0;
%% 7. PZ and TZ regions excluding the lesions
PZTZ = im3dA;
% PZTZ index
pztzIdx = or(PZTZ.Data==1,PZTZ.Data==2);
PZTZ.Data(~pztzIdx) = 0;
%% 8. The lesions of the whole prostate mask
ProstateLesions = im3dA;
ProstateLesions.Data(:) = 0;
ProstateLesions.Data(lesionsIdx) = 1;
%% 9. The lesions of the TZ mask
TZlesionsIdx = xor(TZ.Data,TZHealthy.Data);
TZLesions = im3dA;
TZLesions.Data(:) = 0;
TZLesions.Data(TZlesionsIdx) = 1;
%% 10. The lesions of the PZ mask
PZlesionsIdx = xor(PZ.Data,PZHealthy.Data);
PZLesions = im3dA;
PZLesions.Data(:) = 0;
PZLesions.Data(PZlesionsIdx) = 1;
%% 11. The lesions indices of the whole prostate mask
if sum(lesion1Idx,'all')>0
ProstateLesionIdx1 = im3dA;
ProstateLesionIdx1.Data(:) = 0;
ProstateLesionIdx1.Data(lesion1Idx) = 1;
elseif sum(lesion2Idx,'all')>0
ProstateLesionIdx2 = im3dA;
ProstateLesionIdx1.Data(:) = 0;
ProstateLesionIdx1.Data(lesion2Idx) = 1;
elseif sum(lesion3Idx,'all')>0
ProstateLesionIdx3 = im3dA;
ProstateLesionIdx3.Data(:) = 0;
ProstateLesionIdx3.Data(lesion3Idx) = 1;
end
%% Biopsy data
if exist('ProstateLesionIdx1','var')
% If the case in the sheets list get the info
if numel(currentCaseIdx)>0
% Type of the biopsy
if ~isempty(SheetTableAll.type_biopsi{currentCaseIdx})
BiopsyType = SheetTableAll.type_biopsi{currentCaseIdx};
else
BiopsyType = 'Not avilable';
end
% Number of biopsies
if ~isempty(SheetTableAll.antall_biopsier{currentCaseIdx})
BiopsiesNumber = SheetTableAll.antall_biopsier{currentCaseIdx};
else
BiopsiesNumber ='Not avilable';
end
% True postive Vs. False Positive
if ~isempty(SheetTableAll.biopsisvar{currentCaseIdx})
BiopsyAnswer = SheetTableAll.biopsisvar{currentCaseIdx};
else
BiopsyAnswer = 'Not avilable';
end
% Gleason score
if ~isempty(SheetTableAll.Dersom_positiv_biopsi_Angitt_Gleason_score_for_biopsirunden{currentCaseIdx})
GleasonScore = SheetTableAll.Dersom_positiv_biopsi_Angitt_Gleason_score_for_biopsirunden{currentCaseIdx};
else
GleasonScore = 'Not avilable';
end
% Group grade
if ~isempty(SheetTableAll.Dersom_positiv_biopsi_Angitt_Gradgruppe_for_biopsirunden{currentCaseIdx})
GradeGroup = SheetTableAll.Dersom_positiv_biopsi_Angitt_Gradgruppe_for_biopsirunden{currentCaseIdx};
else
GradeGroup = 'Not avilable';
end
else
BiopsyType = 'Not avilable';
BiopsiesNumber ='Not avilable';
BiopsyAnswer = 'Not avilable';
GleasonScore = 'Not avilable';
GradeGroup = 'Not avilable';
end
end
%% Assign to a structure
if sum(Prostate.Data,'all')>0
vois.Prostate = Prostate;
end
if sum(HealthyProstate.Data,'all')>0
vois.HealthyProstate = HealthyProstate;
end
if sum(TZ.Data,'all')>0
vois.TZ = TZ;
end
if sum(TZHealthy.Data,'all')>0
vois.TZHealthy = TZHealthy;
end
if sum(PZ.Data,'all')>0
vois.PZ = PZ;
end
if sum(PZHealthy.Data,'all')>0
vois.PZHealthy = PZHealthy;
end
if sum(PZTZ.Data,'all')>0
vois.PZTZ = PZTZ;
end
if sum(ProstateLesions.Data,'all')>0
vois.ProstateLesions = ProstateLesions;
end
if sum(TZLesions.Data,'all')>0
vois.TZLesions = TZLesions;
end
if sum(PZLesions.Data,'all')>0
vois.PZLesions = PZLesions;
end
if exist('ProstateLesionIdx1','var')
vois.ProstateLesionIdx1 = ProstateLesionIdx1;
end
if exist('ProstateLesionIdx2','var')
vois.ProstateLesionIdx2 = ProstateLesionIdx2;
end
if exist('ProstateLesionIdx3','var')
vois.ProstateLesionIdx3 = ProstateLesionIdx3;
end
if exist('BiopsyType','var')
vois.BiopsyType = BiopsyType;
end
if exist('BiopsiesNumber','var')
vois.BiopsiesNumber = BiopsiesNumber;
end
if exist('BiopsyAnswer','var')
vois.BiopsyAnswer = BiopsyAnswer;
end
if exist('GleasonScore','var')
vois.GleasonScore = GleasonScore;
end
if exist('GradeGroup','var')
vois.GradeGroup = GradeGroup;
end
%% Save
% Save mat
if ~exist(paths.allVois,'dir')
mkdir(paths.allVois)
end
saveName = fullfile(paths.allVois,[currentCase '_vois.mat']);
save(saveName,'vois')
% Save mhd
% names
savemhdNameWP = fullfile(tpWP,dtpa(jj).name);
savemhdNamePZ = fullfile(tpPZ,dtpa(jj).name);
savemhdNameTZ = fullfile(tpTZ,dtpa(jj).name);
savemhdNameWPh = fullfile(tpWPh,dtpa(jj).name);
savemhdNamePZh = fullfile(tpPZh,dtpa(jj).name);
savemhdNameTZh = fullfile(tpTZh,dtpa(jj).name);
savemhdNamePZTZ = fullfile(tpPZTZ,dtpa(jj).name);
savemhdNameWPl = fullfile(tpWPl,dtpa(jj).name);
savemhdNamePZl = fullfile(tpPZl,dtpa(jj).name);
savemhdNameTZl = fullfile(tpTZl,dtpa(jj).name);
% from im3d to struct
StrDataxWP = elxIm3dToStrDatax(Prostate);
StrDataxPZ = elxIm3dToStrDatax(PZ);
StrDataxTZ = elxIm3dToStrDatax(TZ);
StrDataxWPh = elxIm3dToStrDatax(HealthyProstate);
StrDataxPZh = elxIm3dToStrDatax(PZHealthy);
StrDataxTZh = elxIm3dToStrDatax(TZHealthy);
StrDataxPZTZ = elxIm3dToStrDatax(PZTZ);
StrDataxWPl = elxIm3dToStrDatax(ProstateLesions);
StrDataxPZl = elxIm3dToStrDatax(PZLesions);
StrDataxTZl = elxIm3dToStrDatax(TZLesions);
% from struct to MetaIO
elxStrDataxToMetaIOFile(StrDataxWP, savemhdNameWP, 0);
elxStrDataxToMetaIOFile(StrDataxPZ, savemhdNamePZ, 0);
elxStrDataxToMetaIOFile(StrDataxTZ, savemhdNameTZ, 0);
elxStrDataxToMetaIOFile(StrDataxWPh, savemhdNameWPh, 0);
elxStrDataxToMetaIOFile(StrDataxPZh, savemhdNamePZh, 0);
elxStrDataxToMetaIOFile(StrDataxTZh, savemhdNameTZh, 0);
elxStrDataxToMetaIOFile(StrDataxPZTZ, savemhdNamePZTZ, 0);
elxStrDataxToMetaIOFile(StrDataxWPl, savemhdNameWPl, 0);
elxStrDataxToMetaIOFile(StrDataxPZl, savemhdNamePZl, 0);
elxStrDataxToMetaIOFile(StrDataxTZl, savemhdNameTZl, 0);
%% clean
clearvars -except masterPath paths options SheetTableAll ii jj tpa tpo dtpa dtpo...
tpWP tpWPh tpWPl tpPZ tpPZh tpPZl tpTZ tpTZh tpTZl tpPZTZ
end
end