%These scripts use both fixed threshold and adaptive threshold to index the axon images. 
%The fixed threshold is pre-determined by manually testing against several sample axon images. 
%The adaptive threshold was based on the adaptivethresh.m 
%(http://www.csse.uwa.edu.au/~pk/research/matlabfns/Spatial/adaptivethresh.m).
%The parameters were chosen by testing against sample axon images. 
%Although the results obtained from the adpative and fixed threshold method are not big.
%the adaptive threshold method works better and correctly indexes axons with both strong and weak intensities. 
%The scripts automatically open all tif formatted images in a chosen folder, 
%output thresholded images and save calculated results as Excel spreadsheets. 
%Gang Peng 2011
%Free to use and to modify.

load_folder = pwd;
dirListing = dir(strcat(load_folder,'\*.tif'));
 
manual_threshold = 30;  % enter the threshold number here
threshold_level = manual_threshold/255;
 
axon_sheet = (0:255)'; % initiate axon_sheet to hold raw histogram data
axon_label = {'lumi'}; % initiate header line to store specimen name
specimen_label = {}; % initiate specimen name label
specimen_result = []; % initiate sheet to hold pixel sum data
auto_specimen_result = []; % initiate sheet to hold auto threshold result
 
 
for d = 1:length(dirListing)   
    
    raw_image = imread(dirListing(d).name);  % read in image
    
    image_name = dirListing(d).name;
    image_name = image_name(1:end-4);
    
    axon_label = [axon_label, image_name, 'pixel_sum', 'empty'];
    specimen_label = [specimen_label; image_name];
    
    axon_image = raw_image(:,:,1);  % take the layer contain data
    axon_hist = imhist(axon_image); % get histogram of the data
    point_value = (0:255)'.*axon_hist;
    sum_value = sum(point_value);
    pixel_sum = zeros(256,1);
    for i = 1:256
        pixel_sum(i)= sum_value - point_value(i);
        sum_value = pixel_sum(i);
    end
        
    axon_sheet = [axon_sheet, axon_hist, pixel_sum, zeros(256,1)];
    specimen_result = [specimen_result; pixel_sum(manual_threshold)];
        
    %fixed threshold
    axon_thresholded = im2bw(axon_image, threshold_level);
       
    %automatic adaptive threshold method
    auto_bw_axon = adaptivethresh(axon_image, 10, -20, 'gaussian', 'fixed');
    
    axon_auto_thresholded = sum(axon_image(auto_bw_axon));
    auto_specimen_result = [auto_specimen_result; axon_auto_thresholded];    
    
    % write thresholded images
    axon_bw_name = strcat('bw_', dirListing(d).name);
    axon_auto_bw_name = strcat('autobw_', dirListing(d).name);
    imwrite(axon_thresholded, axon_bw_name, 'tif'); 
    imwrite(auto_bw_axon, axon_auto_bw_name, 'tif');  
end
 
%% prepare and write excel output
% final result
split_m = ones(1, length(dirListing));
result_cell = mat2cell(specimen_result, split_m, 1);
specimen_cell = [specimen_label, result_cell];
 
auto_result_cell = mat2cell(auto_specimen_result, split_m, 1);
auto_specimen_cell = [specimen_label, auto_result_cell];
 
% raw calculation results
[m,n] = size(axon_sheet);
m_divide = ones(1,m);
n_divide = ones(1,n);
sheet_cell = mat2cell(axon_sheet, m_divide, n_divide);
axon_cell = [axon_label; sheet_cell];
 
xlswrite('threshold_results.xls', specimen_cell);
xlswrite('auto_threshold_results.xls', auto_specimen_cell);
xlswrite('axon_raw_data.xls', axon_cell);