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folderSelect
TianyuChe Dec 3, 2023
185e8b8
Update LungAnalyze.m
TianyuChe Dec 3, 2023
f339eb0
Update LungAnalyze.m
TianyuChe Dec 3, 2023
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307 changes: 252 additions & 55 deletions LungAnalyze.m
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Original file line number Diff line number Diff line change
@@ -1,64 +1,261 @@
% Lung CT Image Analyzer App

disp('Welcome to the Lung CT Image Analyzer App!');
disp('This app allows you to view and analyze lung CT images.');
disp('You can choose a lung CT image (1-20) for analysis, and');
disp('the app will display the original image and perform edge detection.');
disp('You can choose to continue analyzing more images or exit the app.');
disp("--------------------------------------------------------------------------------");

while true
% Ask the user for the lung CT image number
image_number = input('Enter the lung CT image number to view (1-20), or enter 0 to exit: ');

% Check if the user wants to exit
if image_number == 0
disp('Exiting program.');
break; % Exit the while loop
% % Lung CT Image Analyzer App
%
% disp('Welcome to the Lung CT Image Analyzer App!');
% disp('This app allows you to view and analyze lung CT images.');
% disp('You can choose a lung CT image (1-20) for analysis, and');
% disp('the app will display the original image and perform edge detection.');
% disp('You can choose to continue analyzing more images or exit the app.');
% disp("--------------------------------------------------------------------------------");
%
% while true
% % Ask the user for the lung CT image number
% image_number = input('Enter the lung CT image number to view (1-20), or enter 0 to exit: ');
%
% % Check if the user wants to exit
% if image_number == 0
% disp('Exiting program.');
% break; % Exit the while loop
% end
%
% % Validate the input
% if image_number < 1 || image_number > 20
% disp('Invalid input. Please enter a number between 1 and 20.');
% continue; % Skip the rest of the loop and ask for input again
% end
%
% % Construct the image filename
% image_filename = sprintf('test_lungs_%02d.jpg', image_number);
%
% % Try to load the image
% try
% % Image Processing Toolbox Add-On
% lungs_img = imread(image_filename);
%
% grayImg = rgb2gray(lungs_img);
%
% detection_types = ["Sobel", "Prewitt", "Roberts", "Log", "Canny", "Canny_old", "Zerocross", "Approxcanny"];
%
% figure;
% subplot(3, 3, 1);
% imshow(grayImg);
% title("Original Image");
%
% plot_number = 2;
% for type = detection_types
% edges = edge(grayImg, type);
% subplot(3, 3, plot_number);
% plot_number = plot_number + 1;
% imshow(edges);
% title(type);
% end
% catch
% % Catch any errors during image loading or processing
% disp('Error loading or processing the image. Please choose another image.');
% continue; % Skip the rest of the loop and ask for input again
% end
%
% % Ask the user if they want to continue
% continue_choice = input('Do you want to generate another lung image? (yes/no): ', 's');
%
% if ~strcmpi(continue_choice, 'yes')
% disp('Exiting program.');
% break; % Exit the while loop
% end
% end
%
% % Image Processing Toolbox Add-On

% Initialize myFolder to an empty string
myFolder = '';

% Keep prompting the user until a valid folder is provided
while ~isfolder(myFolder)
% Prompt the user to manually input the folder path
myFolder = input('Enter the folder path: ', 's');

% Check if the folder exists
if ~isfolder(myFolder)
errorMessage = sprintf('Error: The following folder does not exist:\n%s\nPlease specify a valid folder.', myFolder);
uiwait(warndlg(errorMessage));
end
end
% Get a list of all files in the folder with the desired file name pattern.
filePattern = fullfile(myFolder, '*.png'); % Change to whatever pattern you need.
theFiles = dir(filePattern);
close all;
itemNames = cell(0);
fileNames = cell(0);
circlePercentage = zeros(0);
for k = 1 : length(theFiles)
baseFileName = theFiles(k).name;

fullFileName = fullfile(theFiles(k).folder, baseFileName);



fprintf(1, 'Now reading %s\n', fullFileName);
disp(fullFileName);
% Now do whatever you want with this file name,
% such as reading it in as an image array with imread()

lungs_img = imread(fullFileName);
num_of_circles = check_circles(lungs_img, [0.22 0.6], 0.84, [0.21 0.55], 0.88);
imgPercent = round(num_of_circles/ (13+(k/10)), 4);

circlePercentage(k) = imgPercent;
itemNames(k) = {[baseFileName ' ' num2str(imgPercent*100) '% likely to have mass']};
fileNames(k) = {fullFileName};
end


[~, sortedIndices] = sort(circlePercentage, 'descend');

itemNames = itemNames(sortedIndices);
fileNames = fileNames(sortedIndices);
circlePercentage = circlePercentage(sortedIndices);


%%
% Create a figure
fig = figure('Name', 'GUI', 'units', 'normalized', 'Position', [0.2, 0.2, 0.6, 0.6]);

% Create a listbox
listbox = uicontrol('Style', 'listbox', 'units', 'normalized', 'Position', [0.1, 0.1, 0.8, 0.8], 'String', itemNames, 'UserData', fileNames, 'Callback', @listboxCallback);

% Callback function for listbox selection
function listboxCallback(src, event)
% Get the selected item from the listbox
index = get(src, 'Value');
items = get(src, 'String');
UserData = get(src, 'UserData');
selected_item = items{index};
filename = UserData{index};
disp(filename);
fprintf(1, 'Now reading %s\n', filename);
if(not(isempty(filename)))
lungs_img = imread(filename);
find_circles(lungs_img, selected_item, [0.22 0.6], 0.84, [0.21 0.55], 0.88);
end

end


%%
function [num_of_circles] = find_circles(img, img_name, intensity_bw, circle_sens_bw, intensity_edge, circle_sens_edge)
% find_circles tries to detect circles in the img based on the provided
% thresholds
% find_circles(img, [min_in max_in], circle_sens) adjusts img contrast
% based on [min_in max_in] and detects circles based on circle_sens
% Inputs:
% img : the image to detect circles in
% intensity : [min = 0...1 max = 0...1], min < max; a double vector representing the
% thresholds to base contrast adjustment on
% circle_sens : 0...1; the threshold for circle detection. Greater values
% are less sensitive
% method : the filter to use circle detection on
arguments
img
img_name
intensity_bw (1,2) double = [0.2 0.6]
circle_sens_bw double {mustBeInRange(circle_sens_bw,0,1)} = 0.85
intensity_edge (1,2) double = [0.2 0.6]
circle_sens_edge double {mustBeInRange(circle_sens_edge,0,1)} = 0.85
end
figure('Name', img_name);
set(gcf, 'Position', [360, 360, 1280, 540]);
subplot(1,3,1);
imshow(img);
title("Original");

img = im2gray(img);

% Validate the input
if image_number < 1 || image_number > 20
disp('Invalid input. Please enter a number between 1 and 20.');
continue; % Skip the rest of the loop and ask for input again
% detect circles
% method = 'bw';
img_adjusted_bw = imadjust(img, intensity_bw);
subplot(1,3,2);
% imshow(img_adjusted)
% title("Contrast Adjusted");

img_BW = imbinarize(img_adjusted_bw);
imshow(img_adjusted_bw)
title("Contrast adjusted");
num_of_circles = 0;
[centers, radii] = imfindcircles(img_BW,[9 50], 'ObjectPolarity','bright', 'Sensitivity', circle_sens_bw);
if not(isempty(centers))
num_of_circles = num_of_circles + length(centers);
max_len = min([length(radii) 3]); % only display up to the x strongest circles
centersStrong5 = centers(1:max_len,:);
radiiStrong5 = radii(1:max_len);
viscircles(centersStrong5, radiiStrong5,'EdgeColor','b');
else
disp("No circles found.");
end

% method = 'edge';
img_adjusted_edge = imadjust(img, intensity_edge);
subplot(1,3,3);

img_BW = imbinarize(img_adjusted_edge);
edges = edge(img_BW, 'canny');
imshow(edges)
title("Edge detection");
[centers, radii] = imfindcircles(edges,[9 50], 'ObjectPolarity','bright', 'Sensitivity', circle_sens_edge);

if not(isempty(centers))
num_of_circles = num_of_circles + length(centers);
max_len = min([length(radii) 3]); % only display up to the x strongest circles
centersStrong5 = centers(1:max_len,:);
radiiStrong5 = radii(1:max_len);
viscircles(centersStrong5, radiiStrong5,'EdgeColor','r');

else
disp("No circles found.");
end
end

% Construct the image filename
image_filename = sprintf('test_lungs_%02d.jpg', image_number);

% Try to load the image
try
% Image Processing Toolbox Add-On
lungs_img = imread(image_filename);

grayImg = rgb2gray(lungs_img);

detection_types = ["Sobel", "Prewitt", "Roberts", "Log", "Canny", "Canny_old", "Zerocross", "Approxcanny"];

figure;
subplot(3, 3, 1);
imshow(grayImg);
title("Original Image");

plot_number = 2;
for type = detection_types
edges = edge(grayImg, type);
subplot(3, 3, plot_number);
plot_number = plot_number + 1;
imshow(edges);
title(type);
end
catch
% Catch any errors during image loading or processing
disp('Error loading or processing the image. Please choose another image.');
continue; % Skip the rest of the loop and ask for input again
function [num_of_circles] = check_circles(img, intensity_bw, circle_sens_bw, intensity_edge, circle_sens_edge)
% find_circles tries to detect circles in the img based on the provided
% thresholds
% find_circles(img, [min_in max_in], circle_sens) adjusts img contrast
% based on [min_in max_in] and detects circles based on circle_sens
% Inputs:
% img : the image to detect circles in
% intensity : [min = 0...1 max = 0...1], min < max; a double vector representing the
% thresholds to base contrast adjustment on
% circle_sens : 0...1; the threshold for circle detection. Greater values
% are less sensitive
% method : the filter to use circle detection on
arguments
img
intensity_bw (1,2) double = [0.2 0.6]
circle_sens_bw double {mustBeInRange(circle_sens_bw,0,1)} = 0.85
intensity_edge (1,2) double = [0.2 0.6]
circle_sens_edge double {mustBeInRange(circle_sens_edge,0,1)} = 0.85
end

% Ask the user if they want to continue
continue_choice = input('Do you want to generate another lung image? (yes/no): ', 's');
img = im2gray(img);

img_adjusted_bw = imadjust(img, intensity_bw);

img_BW = imbinarize(img_adjusted_bw);

num_of_circles = 0;
[centers, radii] = imfindcircles(img_BW,[9 50], 'ObjectPolarity','bright', 'Sensitivity', circle_sens_bw);
if not(isempty(centers))
max_len = min([length(radii) 3]); % only display up to the x strongest circles
centersStrong5 = centers(1:max_len,:);
num_of_circles = num_of_circles + length(centersStrong5);
end

img_adjusted_edge = imadjust(img, intensity_edge);

if ~strcmpi(continue_choice, 'yes')
disp('Exiting program.');
break; % Exit the while loop
img_BW = imbinarize(img_adjusted_edge);
edges = edge(img_BW, 'canny');
[centers, radii] = imfindcircles(edges,[9 50], 'ObjectPolarity','bright', 'Sensitivity', circle_sens_edge);

if not(isempty(centers))
max_len = min([length(radii) 3]); % only display up to the x strongest circles
centersStrong5 = centers(1:max_len,:);
num_of_circles = num_of_circles + length(centersStrong5);
end
end