cluster labelling

chaudhuri · Jul 27, 2020 · 8251bfc · 8251bfc
1 parent 1b54e18
commit 8251bfc
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diff --git a/.DS_Store b/.DS_Store
diff --git a/ClusterLabelling.m b/ClusterLabelling.m
@@ -0,0 +1,41 @@
+
+function [ClusterLabels, ClusterParents] = ClusterLabelling(ClusterIntensities,ANO)
+Region = table2array(ANO(:,1));
+ID = table2array(ANO(:,4));
+colHex = table2array(ANO(:,2));
+Children = table2array(ANO(:,5));
+
+Region_index = {}; ClusterLabels = {}; ClusterParents = {};
+for i = 1:length(ClusterIntensities)
+
+    Region_index{end + 1} = find(ID == ClusterIntensities(i));
+    ClusterLabels{end + 1} = Region(Region_index{end});
+
+
+    % if a cluster label is a leaf continue, else leave the label
+    % as it is.
+    ClusterLabel_children = str2num(Children{Region_index{end},1})';
+
+    if(isempty(ClusterLabel_children) == 1) % if the label is a leaf, find parent. 
+
+        dec = 1;
+        arr = Children{Region_index{end} - dec,1};  arr = str2num(arr);
+        cond = isempty(find(ismember(arr,ClusterIntensities(i)), 1));
+        while cond == 1
+            dec = dec + 1;
+            arr = Children{Region_index{end} - dec,1};
+            arr = str2num(arr);
+            cond = isempty(find(ismember(arr,ClusterIntensities(i)), 1));
+
+        end
+        ClusterParents{end + 1} = Region(Region_index{end} - dec,1);
+    else % if the label is a parent, leave parent column in output table empty. 
+        ClusterParents{end +1} = [];
+
+    end
+
+    disp(i);
+end
+
+ClusterLabels = ClusterLabels';
+end
diff --git a/ClusterProportionInPercentages.m b/ClusterProportionInPercentages.m
@@ -1,237 +1,28 @@
-% function combinedtxt = ClusterProportionInPercentages(TemplatesDir,CC,img_cluster)
-function [ClusterLabels, ClusterLabelsPercent] = ClusterProportionInPercentages(TemplatesDir,CC,img_cluster)
-
-
-        % ---------- Annotation Template  ------------ %
-        AnnotatedAllenBrain = spm_vol(strcat(TemplatesDir,'/','wANO.nii'));
-        AnnotatedAllenBrain = spm_read_vols(AnnotatedAllenBrain);
-        ClusterIntensitiesArr = AnnotatedAllenBrain(CC.PixelIdxList{1,img_cluster});
-
-        % Counts & Percent of unique intensities in Cluster intensities array % 
-        a = ClusterIntensitiesArr;
-        [C,ia,ic] = unique(a);
-        a_counts = accumarray(ic,1);
-        value_counts = [C, a_counts];
-        value_counts(:,end+1) = (value_counts(:,2)/sum(value_counts(:,2)))*100;
-        ClusterIntensitiesFreq = value_counts;
-
-        ClusterIntensities = ClusterIntensitiesFreq(:,1);
-        ClusterLabelsPercent = ClusterIntensitiesFreq(:,3);
-
-        % ---------- Allen table  ------------ %
-        ANO = readtable(strcat(TemplatesDir,'/ANO.xlsx'));
-        Region = table2array(ANO(:,1));
-        ID = table2array(ANO(:,4));
-        ID = ID';
 
-        Region_index = {};
-        Labels = {};
-        ClusterLabels = {};
-        for i = 1:length(ClusterIntensities)
-             Region_index{end + 1} = find(ID == ClusterIntensities(i));
-
-             Labels{end + 1} = Region(Region_index{end});
-
-             if(isempty(Labels{i}) == 0)                 
-                 ClusterLabels{end + 1} = Labels{1,i}{1,1};                
-             else                
-                 ClusterLabels{end +1} = 'Background';                     
-             end
-
-
-
-        end
+function [ClusterLabels,ClusterParents, ClusterLabelsPercent] = ClusterProportionInPercentages(TemplatesDir,CC,img_cluster)
+
+
+% ---------- Annotation Template  ------------ %
+AnnotatedAllenBrain = spm_vol(strcat(TemplatesDir,'/','wANO.nii'));
+AnnotatedAllenBrain = spm_read_vols(AnnotatedAllenBrain);
+ClusterIntensitiesArr = AnnotatedAllenBrain(CC.PixelIdxList{1,img_cluster});
+
+% Counts & Percent of unique intensities in Cluster intensities array %
+a = ClusterIntensitiesArr;
+[C,ia,ic] = unique(a);
+a_counts = accumarray(ic,1);
+value_counts = [C, a_counts];
+value_counts(:,end+1) = (value_counts(:,2)/sum(value_counts(:,2)))*100;
+ClusterIntensitiesFreq = value_counts;
+
+ClusterIntensities = ClusterIntensitiesFreq(:,1);
+ClusterIntensities = ClusterIntensities(find(ClusterIntensities));
+ClusterLabelsPercent = ClusterIntensitiesFreq(:,3);
+ClusterLabelsPercent = ClusterLabelsPercent(find(ClusterIntensities));
+while((isempty(ClusterIntensities) == 1) && (isempty(ClusterLabelsPercent) == 1))
+    break;
 end
-
-
 
-
-
-
-
-        %% ----- Old Allen Table ---- %
-
-        %load TREE
-        %[table idxLUT] = buildtable(allen_brain_tree);
-        %ID = extractfield(idxLUT,'id');
-        %ID = ID';
-        %Region = extractfield(idxLUT,'name');
-        %Region = Region';
-
-        % --------------------------- %
+ANO = readtable(strcat(TemplatesDir,'/ANO.xlsx'));
+[ClusterLabels, ClusterParents] = ClusterLabelling(ClusterIntensities,ANO);
 
-
-%%
-
-%         %%%%%%%%% ------ Old Allen table --------%%%%%%%%%
-%         [table idxLUT] = buildtable(allen_brain_tree);
-%         RegionsHierarchyOfAllenBrain = extractfield(idxLUT,'nameinlist')';
-%         ID = {};
-%         for j = 1:length(idxLUT)
-%             ID{end + 1} = extractfield(idxLUT(j),'children');
-%         end
-%         ID = ID';
-%         %%%%%%%%% ----------------------------- %%%%%%%%%%%%%
-%         
-%         
-%         % ------ Cluster Known Constituents.------ %  
-%         ClusterKnownConstituents = {};
-%         for k = 1:length(ClusterIntensitiesArr)
-%             for l = 1:length(ID)
-%                 idx = find(ID{l,1} == ClusterIntensitiesArr(k));
-%                 if(isempty(idx) == 0)
-%                     ClusterKnownConstituents{end + 1} = RegionsHierarchyOfAllenBrain{l,1};
-%                 end
-%             end
-%         end
-%         ClusterKnownConstituents = ClusterKnownConstituents';
-%         % save(strcat('Paths_',ClusterMasks_files{1,i}),'ClusterKnownConstituents');
-%         
-%         %  --Proportion of cluster constituents in voxels-- %
-%         ClusterSizeInVoxels = length(ClusterIntensitiesArr);
-%         hierarchy = ClusterKnownConstituents;
-%         idx_nodes = Nodes_Idx(hierarchy);
-%         KnownCluster_SizeInVoxels = length(idx_nodes{1,1});
-%         UnknownCluster_SizeInVoxels = ClusterSizeInVoxels - KnownCluster_SizeInVoxels;
-%         
-%         % --Names of Cluster Leaves-- %%
-%         root_idx = idx_nodes{1,1};
-%         leaves_idx = [];
-%         for m=2:length(root_idx)
-%             leaves_idx(end + 1) = root_idx(m)-1;
-%         end
-%         Cluster_leaves = hierarchy(leaves_idx);
-%         Cluster_leaves = strip(Cluster_leaves,'left','-');
-%         
-%         name = 'Unknown';
-%         [ClusterUnknown{1:UnknownCluster_SizeInVoxels(1),1}] = deal(name);
-%         SizeOfClusterUnknown = size(ClusterUnknown);
-%         % disp(strcat('Size of unknown: ',num2str(SizeOfClusterUnknown)));
-%         % ClusterUnknown = ClusterUnknown';
-%         ClusterKnown = Cluster_leaves;
-%         ClusterConstituents = [ClusterUnknown;ClusterKnown];
-%         ClusterConstituents = tabulate(ClusterConstituents);
-%         NamesOfClusterConstituents = ClusterConstituents(:,1);
-%         
-%         for z = 2:length(NamesOfClusterConstituents)
-%             ClusterLeaf = NamesOfClusterConstituents{z,1};
-%             
-%             isSubset_Cerebrum = CheckSubset('Cerebrum',ClusterLeaf);
-%             isSubset_BrainStem = CheckSubset('Brain stem',ClusterLeaf);
-%             isSubset_Cerebellum = CheckSubset('Cerebellum',ClusterLeaf);
-%             if(isSubset_Cerebrum == 1)
-%                 isSubset_Isocortex = CheckSubset('Isocortex',ClusterLeaf);
-%                 isSubset_OLF = CheckSubset('Olfactory areas',ClusterLeaf);
-%                 isSubset_HPF = CheckSubset('Hippocampal formation',ClusterLeaf);
-%                 if(isSubset_Isocortex == 1)
-%                     Path = ClusterLeafPath(tree,ClusterLeaf);
-%                     NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 1));
-%                 end
-%                 
-%                 if(isSubset_OLF == 1)
-%                     Path = ClusterLeafPath(tree,ClusterLeaf);
-%                     NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 1));
-%                 end
-%                 
-%                 
-%                 if(isSubset_HPF == 1)
-%                     isSubset_HIP = CheckSubset('Hippocampal region',ClusterLeaf);
-%                     isSubset_RHP = CheckSubset('Retrohippocampal region',ClusterLeaf);
-%                     if(isSubset_HIP == 1)
-%                         isSubset_FC = CheckSubset('Fasciola cinerea',ClusterLeaf);
-%                         isSubset_IG = CheckSubset('Induseum griseum',ClusterLeaf);
-%                         if((isSubset_FC == 1) || (isSubset_IG == 1))
-%                             Path = ClusterLeafPath(tree,ClusterLeaf);
-%                             NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 0));
-%                         else
-%                             Path = ClusterLeafPath(tree,ClusterLeaf);
-%                             NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 1));
-%                         end
-%                     end
-%                     if(isSubset_RHP == 1)
-%                         Path = ClusterLeafPath(tree,ClusterLeaf);
-%                         NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 1));
-%                     end
-%                     
-%                 end
-%                 
-%                 isSubset_CTXsp = CheckSubset('Cortical subplate',ClusterLeaf);
-%                 if(isSubset_CTXsp == 1)
-%                     Path = ClusterLeafPath(tree,ClusterLeaf);
-%                     NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 0));
-%                 end
-%                 
-%                 isSubset_CNU = CheckSubset('Cerebral nuclei',ClusterLeaf);
-%                 if(isSubset_CNU == 1)
-%                     isSubset_CNU = CheckSubset('Olfactory tubercle',ClusterLeaf);
-%                     if(isSubset_CNU == 1)
-%                         Path = ClusterLeafPath(tree,ClusterLeaf);
-%                         NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 1));
-%                     else
-%                         Path = ClusterLeafPath(tree,ClusterLeaf);
-%                         NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 0));
-%                     end
-%                 end
-%             end
-%             
-%             if(isSubset_BrainStem == 1)
-%                 isSubset_TH = CheckSubset('Thalamus',ClusterLeaf);
-%                 isSubset_HY = CheckSubset('Hypothalamus',ClusterLeaf);
-%                 isSubset_MB = CheckSubset('Midbrain',ClusterLeaf);
-%                 isSubset_HB = CheckSubset('Hindbrain',ClusterLeaf);
-%                 
-%                 if(isSubset_TH == 1)
-%                     Path = ClusterLeafPath(tree,ClusterLeaf);
-%                     NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 0));
-%                 end
-%                 %         if(isSubset_HY == 1)
-%                 %
-%                 %         end
-%                 if(isSubset_MB == 1)
-%                     Path = ClusterLeafPath(tree,ClusterLeaf);
-%                     NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 0));
-%                 end
-%                 if(isSubset_HB == 1)
-%                     Path = ClusterLeafPath(tree,ClusterLeaf);
-%                     NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(end - 0));
-%                 end
-%             end
-%             
-%             if(isSubset_Cerebellum == 1)
-%                 isSubset_VERM = CheckSubset('Vermal regions',ClusterLeaf);
-%                 isSubset_HEM = CheckSubset('Hemispheric regions',ClusterLeaf);
-%                 isSubset_CBN = CheckSubset('Cerebellar nuclei',ClusterLeaf);
-%                 if(isSubset_VERM == 1)
-%                     Path = ClusterLeafPath(tree,ClusterLeaf);
-%                     VERM_id = find(contains(Path,'Vermal regions'));
-%                     NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(VERM_id + 1));
-%                 end
-%                 if(isSubset_HEM == 1)
-%                     Path = ClusterLeafPath(tree,ClusterLeaf);
-%                     HEM_id = find(contains(Path,'Hemispheric regions'));
-%                     NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(HEM_id + 1));
-%                 end
-%                 if(isSubset_CBN == 1)
-%                     Path = ClusterLeafPath(tree,ClusterLeaf);
-%                     CBN_id = find(contains(Path,'Cerebellar nuclei'));
-%                     NamesOfClusterConstituents = strrep(NamesOfClusterConstituents,ClusterLeaf,Path(CBN_id + 1));
-%                 end
-%             end
-%         end
-%         ClusterConstituents(:,1) = NamesOfClusterConstituents;
-%         
-%     
-%     
-    %                  % ----- DISPLAY RESULTS ----- % 
-%                  
-%                  %x = cell2mat(ClusterConstituents(:,2));
-%                  % x = tabulate(ClusterLabels);
-%                  ClusterIntensitiesCounts = cell2mat(ClusterIntensitiesFreq(:,2));
-%                  p = pie(ClusterIntensitiesCounts);
-%                  % Get the percent contributions for each pie slice from the String
-%                  % properties of the text objects.Then, specify the text that you want in the cell array txt. Concatenate the text with the associated percent values in the cell array combinedtxt.
-%                  pText = findobj(p,'Type','text');
-%                  percentValues = get(pText,'String');
-%                  NamesOfClusterConstituents = ClusterIntensitiesFreq(:,1);
-%                  txt = strcat(NamesOfClusterConstituents,': ');
-%                  combinedtxt = strcat(txt,percentValues);
diff --git a/Cluster_Overlap_main.m b/Cluster_Overlap_main.m
@@ -37,11 +37,18 @@
 
 
 for img_cluster = 1:NumberOfClusters
-
-    [ClusterLabels,ClusterLabelsPercent] = ClusterProportionInPercentages(TemplatesDir,CC,img_cluster);
+
+    [ClusterLabels,ClusterParents,ClusterLabelsPercent] = ClusterProportionInPercentages(TemplatesDir,CC,img_cluster);
+    if(isempty(ClusterLabels))
+        Cluster_blob_num = cellstr(repmat(['Cluster',' ',num2str(img_cluster)],[1, 1]));
+        ClusterLabels{end + 1} = [];
+        ClusterLabelsPercent = 100;
+        ClusterParents{end + 1} = [];
+    end
     Cluster_blob_num = cellstr(repmat(['Cluster',' ',num2str(img_cluster)],[length(ClusterLabels) 1]));
-    ClusterLabels = ClusterLabels';
-    ClusterImageInfo = table(Cluster_blob_num,ClusterLabels,ClusterLabelsPercent);
+    ClusterParents = ClusterParents';
+    ClusterImageInfo = table(Cluster_blob_num,ClusterLabels,ClusterParents,ClusterLabelsPercent);
+    disp(strcat('Blob','_',num2str(img_cluster),'_','done'));
 
 
     if(img_cluster == 1)

diff --git a/DetectedRegions_gtm.mat b/DetectedRegions_gtm.mat
diff --git a/Int_Isocortex.mat b/Int_Isocortex.mat
diff --git a/Start_ARET.m b/Start_ARET.m
@@ -11,7 +11,7 @@
 
 %% 
 
-DataDir = strcat(DataDir,'/');
+DataDir = strcat(DataDir,'/'); cd(DataDir);
 ToolboxDir = strcat(ToolboxDir,'/');
 global TemplatesDir;
 TemplatesDir = strcat(ToolboxDir,'/','templates');

diff --git a/Striatum ventral region_Mask.nii b/Striatum ventral region_Mask.nii
diff --git a/WM.nii b/WM.nii