From b350b71e6eac42ecc6d78f4d2233204b26d1ed4d Mon Sep 17 00:00:00 2001 From: Greg Burri <greg.burri@gmail.com> Date: Mon, 13 Apr 2015 17:08:35 +0200 Subject: [PATCH] First part> detection of nuclei (parasite) and white blood cells. --- 2002-DiRuberto.pdf | Bin 0 -> 2223699 bytes rapport/main.tex | 103 ++++++++++++++++ src/DetectionOfParasites.m | 155 +++++++++++++++++++++++++ src/DetectionOfSchizonts.m | 0 src/DetectionOfWhiteCells.m | 0 src/IdentificationOfInfectedRedCells.m | 0 src/ParasiteClassification.m | 0 src/SegmentationOfRedCells.m | 0 src/{main.m => Tests.m} | 27 +++-- src/loadImg.m | 2 +- 10 files changed, 272 insertions(+), 15 deletions(-) create mode 100644 2002-DiRuberto.pdf create mode 100644 rapport/main.tex create mode 100644 src/DetectionOfParasites.m create mode 100644 src/DetectionOfSchizonts.m create mode 100644 src/DetectionOfWhiteCells.m create mode 100644 src/IdentificationOfInfectedRedCells.m create mode 100644 src/ParasiteClassification.m create mode 100644 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+\usepackage[utf8]{inputenc} +\usepackage[T1]{fontenc} +\usepackage{lmodern} + +\usepackage{amssymb,amsmath,amsthm} + +\usepackage{graphicx} +\usepackage{listings} +\usepackage{url} +\usepackage{upquote} +\usepackage{color} +\usepackage[usenames,dvipsnames]{xcolor} + +\title{PA} +\author{G.Burri} + + +\begin{document} + +\nocite{*} + +%\maketitle + +Fichier : 1305121398-0001.png + +\begin{figure}[p] + \includegraphics[width=\linewidth]{../output/imgRGBResampled.png} + \caption{Image originale} + \label{fig:imgRGBResampled} +\end{figure} + +\begin{figure}[p] + \includegraphics[width=\linewidth]{../output/gtResampled.png} + \caption{Ground truth} + \label{fig:gtResampled} +\end{figure} + +%%% + +\begin{figure}[p] + \includegraphics[width=\linewidth]{../output/imgH.png} + \caption{Composante teinte (Hue)} + \label{fig:imgH} +\end{figure} + +\begin{figure}[p] + \includegraphics[width=\linewidth]{../output/imgS.png} + \caption{Composante saturation} + \label{fig:imgS} +\end{figure} + +%%% + +\begin{figure}[p] + \includegraphics[width=\linewidth]{../output/imgHFiltered.png} + \caption{Composante teinte filtrée : filtre médian 5x5 + \it{morphological area closing}} + \label{fig:imgHFiltered} +\end{figure} + +\begin{figure}[p] + \includegraphics[width=\linewidth]{../output/imgSFiltered.png} + \caption{Composante saturation filtrée : filtre médian 5x5 + \it{morphological area closing}} + \label{fig:imgSFiltered} +\end{figure} + +%%% + +\begin{figure}[p] + \includegraphics[width=\linewidth]{../granulometry_histogram.png} + \caption{Granulométrie \it{(Pattern spectrum)}} + \label{fig:granulometry_histogram} +\end{figure} + +\begin{figure}[p] + \includegraphics[width=\linewidth]{../output/MH.png} + \caption{Marqueurs des parasites pour la composante teinte suite à l'application d'un maximum regional} + \label{fig:MH} +\end{figure} + +\begin{figure}[p] + \includegraphics[width=\linewidth]{../output/MS.png} + \caption{Marqueurs des parasites pour la composante saturation suite à l'application d'un maximum regional} + \label{fig:MS} +\end{figure} + +\begin{figure}[p] + \includegraphics[width=\linewidth]{../output/MHS.png} + \caption{Intersection entre MH et MS} + \label{fig:MHS} +\end{figure} + +%%% + +\begin{figure}[p] + \includegraphics[width=\linewidth]{../output/THS.png} + \caption{Seuillage afin d'obtenir les parasites et globules blanc (actuellement erroné)} + \label{fig:THS} +\end{figure} + +\end{document} diff --git a/src/DetectionOfParasites.m b/src/DetectionOfParasites.m new file mode 100644 index 0000000..cfe4ac2 --- /dev/null +++ b/src/DetectionOfParasites.m @@ -0,0 +1,155 @@ +% Detection of parasites by means of granulometry and regional maxima. + +%% Parameters +clear; + +imageFolder = '1305121398'; +imageNumber = '0001'; +scaleFactor = 0.6; + +% Load the image and its ground truth. +[imgRGB, gt] = loadImg(imageFolder, imageNumber); + + +%% Extracting of H, S and V components + +% Resample the image and its ground truth. +imgRGBResampled = imresize(imgRGB, scaleFactor); +gtResampled = imresize(gt, scaleFactor); + +imgHSV = rgb2hsv(imgRGBResampled); + +imgH = imgHSV(:, :, 1) * 255; +% We shift the hue to have the greatest value for the nuclei. +hueShiftValue = 195; % 100 +imgH = uint8(mod(255 - imgH + hueShiftValue, 256)); + +imgS = uint8(imgHSV(:, :, 2) * 255); + +% 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) + +% p. 136: median filter to smooth the noise and +% 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. + +% Shading correction with a Top-hat transformation (p. 673). +% imgHFiltered = mmopenth(imgHFiltered, mmsedisk(80, '2D', 'OCTAGON')); +% imgSFiltered = mmopenth(imgSFiltered, mmsedisk(80, '2D', 'OCTAGON')); + + +%% Granulometry +% We use the saturation component to find the red cells mean size. + +redCellMaxSize = 42; % Radius [px]. +funVolume = @(m) sum(sum(m)); + +volImg = funVolume(imgFiltered{2}); + +sizeDistribution = zeros(redCellMaxSize, 1); +parfor k = 1:redCellMaxSize + SE = mmsedisk(k, '2D', 'OCTAGON'); + imgOpened = mmopen(imgFiltered{2}, SE); + A = funVolume(imgOpened); + N = 1 - A / volImg; + sizeDistribution(k) = N; +end + +patternSpectrum = zeros(redCellMaxSize - 1, 1); +for k = 1:redCellMaxSize - 1 + patternSpectrum(k) = abs(sizeDistribution(k + 1) - sizeDistribution(k)); +end + +% The paper choose the biggest red cell size among the possible red cell sizes. (FIXME) +[m, c] = max(patternSpectrum); +c = c + 3; +nucleiRadius = 5; % Find a way to extract this information from the pattern spectrum histogram. (FIXME) + +bar(patternSpectrum); + + +%% Regional extrema +% The size of the SE (c) must be equal to the size of red cells (see granulometry below). + +regionalMaxSE = mmsedisk(c, '2D', 'OCTAGON'); + +parfor i = 1:2 + % This operation is very time consuming! + M{i} = mmregmax(imgFiltered{i}, regionalMaxSE); +end + +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; + +TH = im2bw(imgFiltered{1}, double(muH) / 255); +TS = im2bw(imgFiltered{2}, double(muS) / 255); +THS = TH & TS; + + +%% Output + +mkdir('../output') % Just in case the 'output' directory doesn't exist. + +imwrite(imgRGBResampled, '../output/imgRGBResampled.png') +imwrite(gtResampled, '../output/gtResampled.png') + +imwrite(imgH, '../output/imgH.png') +imwrite(imgS, '../output/imgS.png') + +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]) +colormap(gray); + +subplot(2, 4, 1); +imagesc(imgRGBResampled); +title(['Original: ', imageFolder, '/', imageNumber]); + +subplot(2, 4, 2); +imagesc(imgFiltered{1}); +title('Hue component'); + +subplot(2, 4, 3); +imagesc(imgFiltered{2}); +title('Saturation component'); + +subplot(2, 4, 4); +imagesc(M{1}); +title('MH'); + +subplot(2, 4, 5); +imagesc(M{2}); +title('MS'); + +subplot(2, 4, 6); +imagesc(MHS); +title('MHS'); + +subplot(2, 4, 7); +imagesc(THS); +title('THS'); + +% print("-f1", "-dpng", "Toto.png") + + + + + + + diff --git a/src/DetectionOfSchizonts.m b/src/DetectionOfSchizonts.m new file mode 100644 index 0000000..e69de29 diff --git a/src/DetectionOfWhiteCells.m b/src/DetectionOfWhiteCells.m new file mode 100644 index 0000000..e69de29 diff --git a/src/IdentificationOfInfectedRedCells.m b/src/IdentificationOfInfectedRedCells.m new file mode 100644 index 0000000..e69de29 diff --git a/src/ParasiteClassification.m b/src/ParasiteClassification.m new file mode 100644 index 0000000..e69de29 diff --git a/src/SegmentationOfRedCells.m b/src/SegmentationOfRedCells.m new file mode 100644 index 0000000..e69de29 diff --git a/src/main.m b/src/Tests.m similarity index 84% rename from src/main.m rename to src/Tests.m index 0ba3187..07f4594 100644 --- a/src/main.m +++ b/src/Tests.m @@ -1,3 +1,5 @@ +% These tests are mainly from http://mmorph.com/mxmorph/html/mmdemos/mmdcells.html + % Load the image and its ground truth. imageFolder = '1305121398'; imageNumber = '0001'; @@ -5,7 +7,7 @@ imageNumber = '0001'; % Resample the image and its ground truth. img = imresize(img, 0.2); -gt = imresize(img, 0.2); +gt = imresize(gt, 0.2); % Crop the image (for testing). % img = img(1:300, 1:300, :); @@ -17,12 +19,15 @@ gt = imresize(img, 0.2); img = rgb2hsv(img); imgGray = zeros(h, w); +% hsv = rgb2hsv(rgb); +% S = hsv (:, :, 3); + for i = 1:h for j = 1:w h = img(i, j, 1); s = img(i, j, 2); v = img(i, j, 3); - imgGray(i, j) = v; + imgGray(i, j) = h; % % if (h > 0.861 || h < 0.042) && s > 0.05 && v < 0.85 % imgGray(i, j) = 255 * v; @@ -33,7 +38,7 @@ for i = 1:h end -%% Normalization. +%% Normalization. // Pas forcément utile minimum = min(min(imgGray)); maximum = max(max(imgGray)); imgGrayNorm = uint8(255 * (imgGray - minimum) / (maximum - minimum)); @@ -42,13 +47,15 @@ imgGrayNorm = uint8(255 * (imgGray - minimum) / (maximum - minimum)); %% Morphologic transformation % Top-hat transformation (p 673). -% Try to do some shading correction -a = imgGrayNorm - mmopen(imgGrayNorm, mmsedisk(40)); +% Try to do some shading correction // MMOPENPH +a = imgGrayNorm - mmopen(imgGrayNorm, mmsedisk(40)); % Octagon bcp plus rapide. % Area opening to flatten the cells. b = mmareaopen(a, 200); -% Threshold the image to segment cells. +% Threshold the image to segment cells. // Seuil automatique: graythresh. +% Seuil otsu -> mieux. +% c = mmcmp(uint8(0), '<=', b, '<=', uint8(45)); % Smooth the cells and remove little holes. @@ -112,7 +119,6 @@ mmshow(imgGrayNorm, j); title('Original + j'); - % figure('Position', [100 100 1000 800]) % colormap(gray); % @@ -124,16 +130,9 @@ title('Original + j'); % imagesc(fs); % title('fs'); - - - - - % image(imfuse(img, gt, 'blend')); % colormap('HSV') % image(gt); % colormap([0 0 0; 1 1 1]); % disp('Some tests ...'); - - diff --git a/src/loadImg.m b/src/loadImg.m index 5397aca..1db3a64 100644 --- a/src/loadImg.m +++ b/src/loadImg.m @@ -5,6 +5,6 @@ function [img, gt] = loadImg(name, num) filename = [name, '-', num, '.png']; img = imread([imagesFolder, '/', name, '/', filename]); - gt = imread([groundTruthFolder, '/', name, '/', filename]) ./ 255; + gt = imread([groundTruthFolder, '/', name, '/', filename]); end -- 2.49.0