I am trying to build a system that is automatically take a set of fluorescents images as input, segment them, then calculate the mean intensity value of each image and store them in excel file.
My question here is the segmentation method, when I tried with my data, it include some small random fluroscene as well, I want to exclude them, maybe by including size threshold but I am not sure how, because I even have culstered cells as well.
image_files = dir('A_raw/*.jpg'); % replace 'path/to/images' with the actual path to your images
num_images = length(image_files);
% create a cell array to store the results
results = cell(num_images + 1, 4);
results{1,1} = 'Image Number';
results{1,2} = 'Mean Cell Intensity';
results{1,3} = 'Mean Control Intensity';
results{1,4} = 'Total Area';
for i = 1:num_images
img = imread(fullfile(image_files(i).folder, image_files(i).name));
gray_img = rgb2gray(img);
med_img = medfilt2(gray_img); % noise filtration
clahe_img = adapthisteq(med_img); % enhance contrast
mask = imbinarize(clahe_img);
inv_mask = ~mask;
cell_props = regionprops(mask, gray_img, 'MeanIntensity', 'Area');
cell_intensity = cat(1, cell_props.MeanIntensity);
cell_area = cat(1, cell_props.Area);
cc_inv = bwconncomp(inv_mask);
control_props = regionprops(cc_inv, gray_img, 'Area', 'MeanIntensity');
control_area = cat(1, control_props.Area);
control_intensity = cat(1, control_props.MeanIntensity);
total_area = sum(cell_area) + sum(control_area);
%show the original image and the binary image side by side
figure;
subplot(1, 2, 1);
imshow(img);
title(['Original Image - Image ', num2str(i)]);
subplot(1, 2, 2);
imshow(mask);
title(['Binary Image - Image ', num2str(i)]);
% store the results in the cell array
results{i+1,1} = i;
results{i+1,2} = mean(cell_intensity);
results{i+1,3} = mean(control_intensity);
results{i+1,4} = total_area;
end
% write the results to an Excel file
writecell(results, 'T20_MATLAB.xlsx');
