% Script to load in the volume statistics generated by Samseg during the
% segmentation process.

%% list cases to exclude
% no mathcing, no matching, deformed image
% removecases = {'18-2102','18-2127','18-1343','18-2260','19-0019','19-0138'};
removecases = {'18-2102',... % missing volumes
    '18-2127',...% missing volumes
    '18-2260',...% hemorrhage
    '19-0019',...% missing volumes & hemorrhage
    '18-1705',...% poor segmentation ventricles 
    '18-1754',...% poor segmentation ventricles
    '18-1343',...% poor segmentation deformation
    '19-0138',...% poor segmentation cortex
    '19-0100'... % very large ventricles (biasing)
    };

removaltype = [1,1,1,1,2,2,3,3,4];

removalnotes = {'missing volumes',...
    'missing volumes',...
    'hemorrhage',...
    'missing volumes & hemorrhage',...
    'poor segmentation ventricles',...
    'poor segmentation ventricles',...
    'poor segmentation deformation',...
    'poor segmentation cortex',...
    'very large ventricles (biasing)'
    };

%% setup directories

PHOTO_RECON_HOME=getenv('PHOTO_RECON_HOME');

% segmentation directories
MRIsDir = fullfile(PHOTO_RECON_HOME,'FLAIR_Scan_Data','SAMSEG');
hardDir = fullfile(PHOTO_RECON_HOME,'Results_hard','SAMSEG');
softDir = fullfile(PHOTO_RECON_HOME,'Results','SAMSEG');

% volume directories
MRI_volfolder = fullfile(PHOTO_RECON_HOME,'FLAIR_Scan_Data');
Hrd_rcnfolder = fullfile(PHOTO_RECON_HOME,'Results_hard');

% figure directory
figDir  = fullfile(PHOTO_RECON_HOME,'figures');


%% locate files

dlist_mristats = dir(fullfile(MRIsDir,'*/samseg.stats'));
dlist_hrdstats = dir(fullfile(hardDir,'*/samseg.stats'));
dlist_sftstats = dir(fullfile(softDir,'*/samseg.stats'));

%% read in MRI stats

segVolumeInfo = struct();
segVolumeInfo(length(dlist_mristats)+length(dlist_hrdstats)...
    +length(dlist_sftstats)) = struct();

for il=1:length(dlist_mristats)
   
    [~,segID,~]=fileparts(dlist_mristats(il).folder);
    
    seprtd = regexp(segID(3:end),'_','split');
    
    caseID = [seprtd{1},'-',seprtd{2}];
    
    intable = readtable(fullfile(dlist_mristats(il).folder,dlist_mristats(il).name),'FileType','text');
    
    segVolumeInfo(il).caseID = caseID;
    segVolumeInfo(il).segtype = 'MRI';
    
    %% check if case might need removing
    
    removeindex = ismember(removecases,caseID);
    
    if any(removeindex)
       
        segVolumeInfo(il).removaltype=removaltype(removeindex);
        segVolumeInfo(il).removalnotes=removalnotes{removeindex};
        
    else
        
        segVolumeInfo(il).removaltype=0;
        segVolumeInfo(il).removalnotes='';
        
    end
    
    %% read in volumes 
    
    for jl=1:size(intable,1)
        
        varname = intable{jl,1};
        
        varname = regexp(varname,'# Measure ','split');
        
        varname = [varname{1}{1},varname{1}{2}];
        
        varname = matlab.lang.makeValidName(varname);
        
        segVolumeInfo(il).(varname) = intable.Var2(jl);
        
    end 
    
end

%% read in hard stats


for il=1:length(dlist_hrdstats)
   
    structind = il+length(dlist_mristats);
    [~,segID,~]=fileparts(dlist_hrdstats(il).folder);
    
    seprtd = regexp(segID,'.hard','split');
    
    caseID = seprtd{1};
    
    intable = readtable(fullfile(dlist_hrdstats(il).folder,dlist_hrdstats(il).name),'FileType','text');
    
    segVolumeInfo(structind).caseID = caseID;
    segVolumeInfo(structind).segtype = 'Hard';
    
    %% check if case might need removing
    
    removeindex = ismember(removecases,caseID);
    
    if any(removeindex)
       
        segVolumeInfo(structind).removaltype=removaltype(removeindex);
        segVolumeInfo(structind).removalnotes=removalnotes{removeindex};
        
    else
        
        segVolumeInfo(structind).removaltype=0;
        segVolumeInfo(structind).removalnotes='';
        
    end
    
    %% read in volumes 
    
    for jl=1:size(intable,1)
        
        varname = intable{jl,1};
        
        varname = regexp(varname,'# Measure ','split');
        
        varname = [varname{1}{1},varname{1}{2}];
        
        varname = matlab.lang.makeValidName(varname);
        
        segVolumeInfo(structind).(varname) = intable.Var2(jl);
        
    end 
    
end

%% read in soft stats


for il=1:length(dlist_hrdstats)
   
    structind = il+length(dlist_mristats)+length(dlist_hrdstats);
    [~,segID,~]=fileparts(dlist_sftstats(il).folder);
    
    seprtd = regexp(segID,'_soft','split');
    
    caseID = seprtd{1};
    
    intable = readtable(fullfile(dlist_sftstats(il).folder,dlist_sftstats(il).name),'FileType','text');
    
    segVolumeInfo(structind).caseID = caseID;
    segVolumeInfo(structind).segtype = 'Soft';
    
    %% check if case might need removing
    
    removeindex = ismember(removecases,caseID);
    
    if any(removeindex)
       
        segVolumeInfo(structind).removaltype=removaltype(removeindex);
        segVolumeInfo(structind).removalnotes=removalnotes{removeindex};
        
    else
        
        segVolumeInfo(structind).removaltype=0;
        segVolumeInfo(structind).removalnotes='';
        
    end
    
    %% read in volumes 
    
    for jl=1:size(intable,1)
        
        varname = intable{jl,1};
        
        varname = regexp(varname,'# Measure ','split');
        
        varname = [varname{1}{1},varname{1}{2}];
        
        varname = matlab.lang.makeValidName(varname);
        
        segVolumeInfo(structind).(varname) = intable.Var2(jl);
        
    end 
    
end

%% write out table 

T = struct2table(segVolumeInfo);

writetable(T,fullfile(figDir,'UWphoto_fullSegmentationStats.xlsx'))


%% remove bad apples
strfields = fieldnames(segVolumeInfo);

removeindex = ismember({segVolumeInfo.caseID},removecases);

% processtruct = instructure(~removeindex);



%% load in spreadsheets

infoTable=readtable(fullfile(figDir,'NP data for reconstruction cohort.xlsx'));
crosswalk=readtable(fullfile(figDir,'crosswalk.xlsx'));



%% match up case IDs

caseID = cell(size(infoTable,1),1);

for il=1:size(infoTable,1)
   
    caseID{il} = crosswalk.npNumber1(crosswalk.tissueCode==infoTable.TissueCode(il));
    
    
end

matchedInfo = [cell2table(caseID),infoTable];

%% get left right averages

% segVolumeInfo = processtruct;

flag_fieldsToAverage_left = startsWith(strfields,'Left_');

fieldsToAverage_left=strfields(flag_fieldsToAverage_left);

fieldendings = regexp(strfields(flag_fieldsToAverage_left),'Left_','split');

for il=1:length(fieldendings)
    fieldendings{il}=fieldendings{il}{2};
end

for il = 1:length(fieldsToAverage_left)  
   
    fieldToAverage_right = strfields{startsWith(strfields,'Right_') &...
        endsWith(strfields,fieldendings(il))};
    
    for jl = 1:length(segVolumeInfo)
        leftVal = segVolumeInfo(jl).(fieldsToAverage_left{il});
        rightVal = segVolumeInfo(jl).(fieldToAverage_right);
        
        segVolumeInfo(jl).(['Average_',fieldendings{il}]) = mean([leftVal,rightVal]);
    
    end
end



%% get volume adjustment factor
% During reconstruction using a hard mask some affine deformation is
% applied to the MRI mask at the same time as the individual slices. This
% is to account for gross changes in the brain between scanning and
% dissection. 
%
% This means volumes from the MRI segmentations should be adjusted to
% correlate properly with the photo segmentations. The correction factor is
% 
% adjustment = prod(MRI.volres)/prod(photo.volres)
%
% giving the ratio between MR and photo voxel volume. The adjusted photo
% volumes are then
%
% vol_corrected = adjustment * volume_photo

for il=1:length(segVolumeInfo)

    if strcmp(segVolumeInfo(il).segtype,'Hard')
        
        MR_ID_parts = regexp(segVolumeInfo(il).caseID,'-','split');
        MR_ID = ['NP',MR_ID_parts{1},'_',MR_ID_parts{2}];
        
        dlist_mri = dir(fullfile(MRI_volfolder,[MR_ID,'.rotated.mgz']));
        mri_vol = MRIread(fullfile(dlist_mri.folder,dlist_mri.name));
        
        dlist_hrd = dir(fullfile(Hrd_rcnfolder,segVolumeInfo(il).caseID,...
            '*warped_ref*'));
        hrd_vol = MRIread(fullfile(dlist_hrd.folder,dlist_hrd.name));
        
        tempadjustfactor = prod(mri_vol.volres)/prod(hrd_vol.volres);
        
        segVolumeInfo(il).volumeAdjustmentFactor = tempadjustfactor;
        
    else
        segVolumeInfo(il).volumeAdjustmentFactor = 1;
    end

end

%% save stuff

save(fullfile(figDir,'AdjustedCaseStats.mat'),'segVolumeInfo',...
    'matchedInfo','removecases')