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mean_array_code.m
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mean_array_code.m
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close all
clear all
srcFile = dir('G:\Shared drives\INSTEM-IISERK-COLLAB\Analysis-Cells-16022021\ANALYSIS\method 1\Doxorubicin-20-nM-120-hours-18-hours-Cycloheximide-+ve\*.tif');
image_folder ='G:\Shared drives\INSTEM-IISERK-COLLAB\Analysis-Cells-16022021\ANALYSIS\method 1\Doxorubicin-20-nM-120-hours-18-hours-Cycloheximide-+ve\'
%specify folder for saving
% memb_save_folder = 'D:\swarang\golgi_membrane\yo\Analysis-Cells-16012021\trial_run\memb_data';
% golgi_save_folder = 'D:\swarang\golgi_membrane\yo\Analysis-Cells-16012021\trial_run\golgi_data';
golgi_mean=[]
memb_mean=[]
file_name_arr=[]
for n=1:length(srcFile)
% baseFileName="Cell4"
% FileName=baseFileName+'.tif'
% change this to the file name of image file
FileName = strcat(image_folder,srcFile(n).name);
% read image and split channels
I1=imread(FileName,1);
I2=imread(FileName,2);
% maxI1=max(I1, [], 'all')
% maxI2=max(I2, [], 'all')
% max_absolute=max(maxI1,maxI2)
% --------------------------------------------------------------------------------------------------
%%%%%%%%%%%%%%%%%% GOLGI SECTION %%%%%%%%%%%%%%%%%%
% --------------------------------------------------------------------------------------------------
[level,metric] = multithresh(I2); %multi level thresholding of red (golgi) channel
seg_I2 = imquantize(I2,level);
RGB = label2rgb(seg_I2);
% figure;
% % imshow(seg_I2,[])
% imshow(RGB)
seg=seg_I2-1;
% var_golgi = (immultiply(uint16(seg_I2),I1))./2; %multiply sugmented red channel with original green channel
golgi = immultiply(uint16(seg),I1);
% max_golgi=max(golgi, [], 'all')
% max_golgi=max(var_golgi, [], 'all')
% golgi=var_golgi./max_golgi;
% figure
% imshow(golgi,[])
% file=golgi;
% imwrite(file,baseFileName+'golgi','tiff'); %write segmented golgi (red) channel image to a tiff file
% --------------------------------------------------------------------------------------------------
%%%%%%%%%%%%%%%% MEMBRANE SECTION %%%%%%%%%%%%%%%%%%
% --------------------------------------------------------------------------------------------------
Golgi_rem_Image=I1-(golgi);
% figure;
% imshow(Golgi_rem_Image,[])
% Get the green channel.
% imhist(grayImage);
% Get a binary image.
mask = Golgi_rem_Image > 100;
% Take only the largest blob. Use 4-connectivity.
mask = bwareafilt(mask, 1, 4);
% To find the average length and width we need to get the Euclidean distance transform and the skeleton of it.
edtImage = bwdist(~mask);
edtImage=edtImage./max(edtImage,[],'all');
% var_memb = (immultiply(uint16(edtImage),I1))./(2^4);
memb = immultiply(uint16(edtImage),Golgi_rem_Image);
% max_memb=max(memb, [], 'all')
% max_memb=max(var_memb, [], 'all')
% memb=var_memb./max_memb;
% figure
% imshow(memb,[]);
% path=strcat(image_folder, srcFile(n).name)
file_name_arr=[file_name_arr, string(srcFile(n).name)];
% path_memb=strcat(memb_save_folder, srcFile(n).name)
% path_golgi=strcat(golgi_save_folder, srcFile(n).name)
% %%%%%%%%%% MEMBRANE HISTOGRAM %%%%%%%%%%
% figure
h_memb=histogram(memb,'BinWidth',5, 'BinLimits',[1,4090]); %plot histogram of membrane
title(string(srcFile(n).name) + ' histogram of membrane')
data_memb = h_memb.Values;
counts_memb = data_memb;
centerBinGrayLevels_memb = (h_memb.BinEdges(1:end-1) + h_memb.BinEdges(2:end)) / 2;
meanBinnedGrayLevel_memb = sum(centerBinGrayLevels_memb .* counts_memb) / sum(counts_memb);
memb_mean=[memb_mean,meanBinnedGrayLevel_memb];
% xline(meanBinnedGrayLevel_memb, 'Color', 'g', 'LineWidth', 2);
% saveas(gcf, string(path)+'_memb_mean.png')
% close
% %%%%%%%%%% GOLGI HISTOGRAM %%%%%%%%%%
% figure
h_golgi=histogram(golgi,'BinWidth',5, 'BinLimits',[1,4090]); %plot histogram of golgi
% title(string(srcFile(n).name) +' histogram of golgi')
data_golgi = h_golgi.Values;
counts_golgi = data_golgi;
centerBinGrayLevels_golgi = (h_golgi.BinEdges(1:end-1) + h_golgi.BinEdges(2:end)) / 2;
meanBinnedGrayLevel_golgi = sum(centerBinGrayLevels_golgi .* counts_golgi) / sum(counts_golgi);
% xline(meanBinnedGrayLevel_golgi, 'Color', 'r', 'LineWidth', 2);
golgi_mean=[golgi_mean,meanBinnedGrayLevel_golgi];
% saveas(gcf, string(path) + '_golgi_mean.png')
% close
% data_golgi_filename=string(path_golgi)+'.csv';
% data_memb_filename=string(path_memb)+'.csv';
% csvwrite(string(path)+'_golgi_data.csv', transpose(data_golgi));
% csvwrite(string(path)+'_memb_data.csv', transpose(data_memb));
end
% imwrite(memb,baseFileName+'membrane.tif','tiff')
csvwrite('memb_mean_data_4090.csv', transpose(memb_mean));
csvwrite('golgi_mean_data_4090.csv', transpose(golgi_mean));
writematrix(transpose(file_name_arr), 'file_names.csv');
mean_ratio=golgi_mean./memb_mean;
csvwrite('mean_ratio_4090.csv', transpose(mean_ratio));