Implmentation of the detection of WBC and schizonts.

diff --git a/src/DetectionOfParasites.m b/src/DetectionOfParasites.m
index fd94e0e..bdb2a51 100644 (file)
--- a/src/DetectionOfParasites.m
+++ b/src/DetectionOfParasites.m
@@ -1,15 +1,27 @@
 % Detection of parasites by means of granulometry and regional maxima.
-function [THS, c] = DetectionOfParasites(imgRGB, gt)
+% Inputs:
+%  imgRGB: The image of a blood sample.
+% Outputs:
+%  THS: Parasites of all types and WBC (mask).
+%  c: Typical red cell radius [px].
+function [THS, c] = DetectionOfParasites(imgRGB)
 
+    imwrite(imgRGB, '../output/imgRGB.png')
+    
     %% Extracting of H, S and V components
     imgHSV = rgb2hsv(imgRGB);
 
     imgH = imgHSV(:, :, 1) * 255;
     % We shift the hue to have the greatest value for the nuclei.
-    hueShiftValue = 195; % 100
+    hueShiftValue = 175; % 100
     imgH = uint8(mod(255 - imgH + hueShiftValue, 256));
+    imwrite(imgH, '../output/imgH.png')
 
     imgS = uint8(imgHSV(:, :, 2) * 255);
+    imwrite(imgS, '../output/imgS.png')
+    
+    imgV = uint8(255 - imgHSV(:, :, 3) * 255);
+    imwrite(imgV, '../output/imgV.png')
 
     % imgV = uint8(imgHSV(:, :, 3) * 255); % The value component isn't used.
     % imgH = 255 - imgV; % We use the value component instead of the hue one (just for testing)
@@ -18,8 +30,14 @@ function [THS, c] = DetectionOfParasites(imgRGB, gt)
     % area closing to enhance the bright objects and make flatter, darker and cleaner the image background.
     imgFiltered{1} = mmareaclose(medfilt2(imgH, [5, 5]), 400); % Hue.
     imgFiltered{2} = mmareaclose(medfilt2(imgS, [5, 5]), 400); % Saturation.
-
+    imgFiltered{3} = mmareaclose(medfilt2(imgV, [5, 5]), 400); % Value.
+    
+    imwrite(imgFiltered{1}, '../output/imgHFiltered.png');
+    imwrite(imgFiltered{2}, '../output/imgSFiltered.png');
+    imwrite(imgFiltered{3}, '../output/imgVFiltered.png');
+    
     % Shading correction with a Top-hat transformation (p. 673).
+    % Not in the article -> disable for the moment, not needed.
     % imgHFiltered = mmopenth(imgHFiltered, mmsedisk(80, '2D', 'OCTAGON'));
     % imgSFiltered = mmopenth(imgSFiltered, mmsedisk(80, '2D', 'OCTAGON'));
 
@@ -48,7 +66,7 @@ function [THS, c] = DetectionOfParasites(imgRGB, gt)
 
     % The paper choose the biggest red cell size among the possible red cell sizes. (FIXME)
     [m, c] = max(patternSpectrum);
-    c = c + 3;
+    % c = c + 3;
     nucleiRadius = 5; % Find a way to extract this information from the pattern spectrum histogram. (FIXME)
 
     bar(patternSpectrum);
@@ -59,7 +77,7 @@ function [THS, c] = DetectionOfParasites(imgRGB, gt)
 
     regionalMaxSE = mmsedisk(c, '2D', 'OCTAGON');
 
-    parfor i = 1:2
+    parfor i = 1:3
         % This operation is very time consuming!
         M{i} = mmregmax(imgFiltered{i}, regionalMaxSE);
     end
@@ -67,37 +85,20 @@ function [THS, c] = DetectionOfParasites(imgRGB, gt)
     nucleiSE = mmsedisk(nucleiRadius, '2D', 'OCTAGON');
     MHS = mmdil(M{1}, nucleiSE) & mmdil(M{2}, nucleiSE);
 
-    volumeMHS = funVolume(~MHS);
-    muH = funVolume(uint8(~MHS) .* imgFiltered{1}) / volumeMHS;
-    muS = funVolume(uint8(~MHS) .* imgFiltered{2}) / volumeMHS;
+    volumeMHS = funVolume(MHS);
+    muH = funVolume(uint8(MHS) .* imgFiltered{1}) / volumeMHS;
+    muS = funVolume(uint8(MHS) .* imgFiltered{2}) / volumeMHS;
 
     TH = im2bw(imgFiltered{1}, double(muH) / 255);
     TS = im2bw(imgFiltered{2}, double(muS) / 255);    
     
-    THS = TH & TS; % Parasites of all type and WBC.
-
-
-    %% Output
-
-    mkdir('../output') % Just in case the 'output' directory doesn't exist.
-
-    imwrite(imgRGB, '../output/imgRGB.png')
-    imwrite(gt, '../output/gt.png')
-
-    imwrite(imgH, '../output/imgH.png')
-    imwrite(imgS, '../output/imgS.png')
+    THS = TH & TS;
 
     imwrite(M{1}, '../output/MH.png')
-    imwrite(imgFiltered{1}, '../output/imgHFiltered.png');
-
     imwrite(M{2}, '../output/MS.png')
-    imwrite(imgFiltered{2}, '../output/imgSFiltered.png');
-
     imwrite(MHS, '../output/MHS.png')
-
     imwrite(THS, '../output/THS.png')
 
-
     %% Display
 
 %     figure('Position', [100 100 1600 800])

diff --git a/src/DetectionOfSchizonts.m b/src/DetectionOfSchizonts.m
index e69de29..4d94f08 100644 (file)
--- a/src/DetectionOfSchizonts.m
+++ b/src/DetectionOfSchizonts.m
@@ -0,0 +1,41 @@
+% Inputs:
+function [schizonts] = DetectionOfSchizonts(THS, c)    
+
+    redCellsSE = mmsedisk(c, '2D', 'OCTAGON');    
+    schizonts = zeros(size(THS), 'uint8');    
+    
+    %% Extract all sets.
+    sets = {};
+    n = 1;
+    remainingTHS = THS;
+    marker = false(size(THS));    
+    while 1
+        [i, j] = find(remainingTHS, 1);    
+        if ~isempty(i)
+            marker(i, j) = 1;
+            sets{n} = mminfrec(marker, remainingTHS); %#ok<AGROW> % Reconstruction by dilation. 
+            remainingTHS = remainingTHS & ~sets{n};
+            n = n + 1;
+            marker(i, j) = 0;
+        else
+            break
+        end
+    end
+    
+    %% Check the Hausdorff distance between each set combination by dilation.
+    for i = 1:length(sets)
+        setA = sets{i};
+        dilatedSetA = mmdil(setA, redCellsSE);
+        for j = 1:length(sets)
+            setB = sets{j};
+            if setB == setA
+                continue
+            end
+            if (dilatedSetA & setB) == setB %#ok<AND2> % If B is a subset of A -> there are both in a Hausdorff distance of 2*c.
+                schizonts = schizonts | setA | setB;
+            end
+        end
+    end    
+    
+    imwrite(schizonts, '../output/schizonts.png')
+end
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diff --git a/src/DetectionOfWhiteCells.m b/src/DetectionOfWhiteCells.m
index e32eb25..b139bc9 100644 (file)
--- a/src/DetectionOfWhiteCells.m
+++ b/src/DetectionOfWhiteCells.m
@@ -1,3 +1,14 @@
-function [] = DetectionOfParasites()
+% Inputs:
+%  c: The typical red cell radius [px].
+function [WBCSmoothed] = DetectionOfWhiteCells(THS, c)    
+    redCellsSE = mmsedisk(c - 8, '2D', 'OCTAGON');
+
+    % The white cells may not be correctly marked in the case they have a very special shape (oblong).
+    WBCMarker = mmero(THS, redCellsSE); % Erosion to keep only fragments of white cells.
+    WBC = mminfrec(WBCMarker, THS); % Reconstruction by dilation.
+        
+    % Morphological smoothing (Hole filling).
+    WBCSmoothed = mmclohole(WBC);    
     
+    imwrite(WBCSmoothed, '../output/whiteCells.png')
 end
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