blood vesselImage Processing Toolboxtortuosity
% function testRGBImage()
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
workspace; % Make sure the workspace panel is showing.
format long g;format compact;fontSize = 20;%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = 'ricesam2.jpg';folder = fileparts(which(baseFileName)); % Determine where demo folder is (works with all versions).
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; endend%=======================================================================================
% Read in demo image.
rgbImage = imread(fullFileName);% Get the dimensions of the image.
[rows, columns, numberOfColorChannels] = size(rgbImage);% Display the original image.
subplot(2, 2, 1);imshow(rgbImage, []);axis on;caption = sprintf('Original Color Image, %s', baseFileName);title(caption, 'FontSize', fontSize, 'Interpreter', 'None');% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0.05 1 0.95]);% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')drawnow;hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Get a mask of the blue channel
binaryImage = rgbImage(:,:,3) < 173;% Get rid of junk near edge of image.
binaryImage = imclearborder(binaryImage);% Display the mask image.
subplot(2, 2, 2);imshow(binaryImage, []);axis on;caption = sprintf('Binary Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');% Filter out blobs smaller than 100 or bigger than 1000
binaryImage = bwareafilt(binaryImage, [100, 1000]);% Display the mask image.subplot(2, 2, 3);imshow(binaryImage, []);axis on;caption = sprintf('Size Filtered Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');% Find the areas of what's left.
props = regionprops(binaryImage, 'Area');allAreas = [props.Area]% Display the distribution of areas.
subplot(2, 2, 4);histogram(allAreas);axis on;grid on;title('Histogram of Areas', 'FontSize', fontSize, 'Interpreter', 'None');message = sprintf('The smallest area = %.1f pixels', min(allAreas));uiwait(helpdlg(message));
% This demo computes the tortuosity of a snake-like shape by dividing the actual longest spine distance by the straight line distance between the endpoints.
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 = 15;%--------------------------------------------------------------------------------------------------------
% READ IN IMAGE
folder = pwd;baseFileName = 'worm.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; endend% Read in the image from disk. If storedColorMap is not empty, it's an indexed image with a stored colormap.
[grayImage, storedColorMap] = imread(fullFileName);if ~isempty(storedColorMap) grayImage = ind2rgb(grayImage, storedColorMap);end% 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.
hFig = figure;subplot(1, 2, 1);imshow(grayImage, []);title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');impixelinfo;hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;%--------------------------------------------------------------------------------------------------------% SEGMENTATION
% Binarize the image
binaryImage = imbinarize(grayImage);% Take the largest blob only.
binaryImage = bwareafilt(binaryImage, 1);% Fill holes, if any.
binaryImage = imfill(binaryImage, 'holes');% Display the binary image.
subplot(1, 2, 1);imshow(binaryImage, []);title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');axis('on', 'image');% Now skeletonize
skelImage = bwskel(binaryImage); % First guess. Will have short spurs.
% First get the area of the skeleton and take half of it to be the longest spine length.
% This will get rid of all spurs.
MinBranchLength = round(sum(skelImage(:))/2)% Now take the skeleton again using that min branch length we just computed.
skelImage = bwskel(binaryImage, 'MinBranchLength', MinBranchLength);% Display the skeleton image.
subplot(1, 2, 2);imshow(skelImage, []);title('Skeleton Image', 'FontSize', fontSize, 'Interpreter', 'None');axis('on', 'image');% Find the endpoints
endpointImage = bwmorph(skelImage, 'endpoints');[rows, columns] = find(endpointImage)% Draw a red line between them.
hold on;plot(columns, rows, 'r-', 'LineWidth', 2);% Find the spine length.
% (Would be more accurate to find the spine length by traversing it.)
spineLength = sum(skelImage(:))% Compute the straight line distance.
straightLineDistance = sqrt((columns(2) - columns(1))^2 + (rows(2) - rows(1))^2)% Compute the tortuosity
tortuosity = spineLength / straightLineDistancecaption = sprintf('Skeleton Image. Tortuosity = %f', tortuosity);title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
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