MATLAB: How to denoise this cell image and generate connected regions

drosophilaimage noise reductionImage Processing Toolboximage segmentation

I am processing images of Drosophila embryos to achieve precise positioning of the nucleus in the embryo. But at present, I have a problem in generating accurate nuclei connectivity areas, and it is impossible to accurately tell the true nuclear fluorescence signal from noise.

Thanks in advance!

Best Answer

Threshold it and call imclose(). Untested code:

mask = grayImage > someValue;
se = strel('disk', 5, 0);
mask = imclose(mask, se);
mask = bwareaopen(mask, 4) % Get rid of blobs smaller than 4 pixels.
props = regionprops(mask, 'Centroid');
xy = vertcat(props.Centroid)

Related Solutions

MATLAB: Detection of Particle Orientation

Use regionprops():

% Code to detect angle of a blob.
% By Image Analyst
clc;    % Clear the command window.
fprintf('Beginning to run %s.m ...\n', mfilename);
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 15;
%--------------------------------------------------------------------------------------------------------

%    READ IN IMAGE
folder = pwd;
baseFileName = 'ZoomIn_100f.jpg';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
	% The file doesn't exist -- didn't find it there in that folder.
	% Check the entire search path (other folders) for the file by stripping off the folder.
	fullFileNameOnSearchPath = baseFileName; % No path this time.
	if ~exist(fullFileNameOnSearchPath, 'file')
		% Still didn't find it.  Alert user.
		errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
		uiwait(warndlg(errorMessage));
		return;
	end
end
grayImage = imread(fullFileName);
% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage);
if numberOfColorChannels > 1
	% It's not really gray scale like we expected - it's color.
	% Use weighted sum of ALL channels to create a gray scale image.
% 	grayImage = rgb2gray(grayImage);
	% ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
	% which in a typical snapshot will be the least noisy channel.
	grayImage = grayImage(:, :, 1); % Take red channel.
end
% Crop it to the right lines.
% grayImage = grayImage(1750:2250, 800:end);
subplot(2, 2, 1);
imshow(grayImage, []);
impixelinfo;
title('Red Channel Image', 'FontSize', fontSize, 'Interpreter', 'None');
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.

drawnow;
subplot(2, 2, 2);
imhist(grayImage);
grid on;
title('Histogram of Original Image', 'FontSize', fontSize, 'Interpreter', 'None');
%--------------------------------------------------------------------------------------------------------
%    SEGMENTATION OF IMAGE
% Get a binary image by interactively thresholding using the function at
% https://www.mathworks.com/matlabcentral/fileexchange/29372-thresholding-an-image
% 91 seems good for this image.
lowThreshold = 91;
highThreshold = 255;
% [lowThreshold, highThreshold] = threshold(lowThreshold, highThreshold, grayImage)
mask = grayImage > lowThreshold & grayImage < highThreshold;
mask = imclearborder(mask);
mask = imfill(mask, 'holes');
% Take largest blobs.
mask = bwareafilt(mask, 1);
subplot(2, 2, 3);
imshow(mask, []);
impixelinfo;
caption = sprintf('Mask of White SemiCircles');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
% Measure centroid and orientation.
props = regionprops(mask, 'Centroid', 'Orientation')
xCenter = props.Centroid(1);
yCenter = props.Centroid(2);
hold on;
plot(xCenter, yCenter, 'r+', 'MarkerSize', 40, 'LineWidth', 2);
% Display the masked image.
subplot(2, 2, 4);
overlayImage = imoverlay(grayImage, mask, 'r');
imshow(overlayImage, []);
impixelinfo;
caption = sprintf('Masked Image.  Angle = %.2f degrees.', props.Orientation);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
% Make a line at that angle at the centroid.
slope = tan(props.Orientation)
x = 1 : columns;
y = slope * (x - xCenter) + yCenter;
hold on;
plot(x, y, 'r-', 'LineWidth', 2);
fprintf('Done running %s.m ...\n', mfilename);

MATLAB: Obtain average image threshold without the background

Try this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 22;
%--------------------------------------------------------------------------------------------------------

%    READ IN IMAGE
folder = pwd;
baseFileName = 'image.png';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
	% The file doesn't exist -- didn't find it there in that folder.
	% Check the entire search path (other folders) for the file by stripping off the folder.
	fullFileNameOnSearchPath = baseFileName; % No path this time.
	if ~exist(fullFileNameOnSearchPath, 'file')
		% Still didn't find it.  Alert user.
		errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
		uiwait(warndlg(errorMessage));
		return;
	end
end
grayImage = imread(fullFileName);
% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage);
if numberOfColorChannels > 1
	% It's not really gray scale like we expected - it's color.
	% Use weighted sum of ALL channels to create a gray scale image.
	grayImage = rgb2gray(grayImage);
	% ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
	% which in a typical snapshot will be the least noisy channel.
	% grayImage = grayImage(:, :, 2); % Take green channel.
end
% Display the image.
subplot(2, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
%--------------------------------------------------------------------------------------------------------
%    SEGMENTATION OF IMAGE
% Get a binary image of just the blob and not including the black background or the white surround.
mask = grayImage > 0 & grayImage < 255;  %imbinarize(grayImage);
subplot(2, 2, 2);
imshow(mask, []);
impixelinfo;
title('Initial Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
% Display histogram of image but only the image within the mask
subplot(2, 3, 4);
histogram(grayImage(mask), 0:255);
grid on;
title('Histogram of gray image', 'FontSize', fontSize);
% Now get the threshold
thresh = 255 * graythresh(grayImage(mask))
% Put a red line there at the threshold
xline(thresh, 'Color', 'r', 'LineWidth', 2);
% Get a binary image of the bright stuff
brightStuff = grayImage >= thresh & mask;
subplot(2, 3, 5);
imshow(brightStuff, []);
impixelinfo;
title('Bright Pixels in Region', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
subplot(2, 3, 6);
darkStuff = ~brightStuff & mask;
imshow(darkStuff, []);
impixelinfo;
title('Dark Pixels in Region', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;

Best Answer

Related Solutions

MATLAB: Detection of Particle Orientation

MATLAB: Obtain average image threshold without the background

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