Matlab and ImageJ detecting bone fracture - matlab

Question

I'm trying to detect a fracture in a picture using imageJ and Matlab, both of them are required. Here is the original image:
I already established the connection between matlab and imageJ and I've opened the image on imageJ and started by doing some things. First, I used the Find Edges function in imageJ menu to get an outline of the bone. After I did a constrast enhancement to enhance the outline. My problem now is, having only an outline and a black background how can I make an algorithm or something like it that will tell me that the lines don't connect? (meaning there is a fracture in the bone). I did something similar to what is on this video in the part when he ticks the sobel edge detection.
https://www.youtube.com/watch?v=Hxn2atZl5us

Answer 1

Gave it a shot in MATLAB only. You can use the Hough transform to find what the largest-contributing angles are to the edge-filtered image, then use that information to go one step more and detect where the break is with some typical image processing tricks.
No promises on how this will work on any images that are not the one that you provided, but the steps are reasonable to refine for additional sample breadth.
img = imread('http://i.stack.imgur.com/mHo7s.jpg');
ImgBlurSigma = 2; % Amount to denoise input image
MinHoughPeakDistance = 5; % Distance between peaks in Hough transform angle detection
HoughConvolutionLength = 40; % Length of line to use to detect bone regions
HoughConvolutionDilate = 2; % Amount to dilate kernel for bone detection
BreakLineTolerance = 0.25; % Tolerance for bone end detection
breakPointDilate = 6; % Amount to dilate detected bone end points
%%%%%%%%%%%%%%%%%%%%%%%
img = (rgb2gray(img)); % Load image
img = imfilter(img, fspecial('gaussian', 10, ImgBlurSigma), 'symmetric'); % Denoise
% Do edge detection to find bone edges in image
% Filter out all but the two longest lines
% This feature may need to be changed if break is not in middle of bone
boneEdges = edge(img, 'canny');
boneEdges = bwmorph(boneEdges, 'close');
edgeRegs = regionprops(boneEdges, 'Area', 'PixelIdxList');
AreaList = sort(vertcat(edgeRegs.Area), 'descend');
edgeRegs(~ismember(vertcat(edgeRegs.Area), AreaList(1:2))) = [];
edgeImg = zeros(size(img, 1), size(img,2));
edgeImg(vertcat(edgeRegs.PixelIdxList)) = 1;
% Do hough transform on edge image to find angles at which bone pieces are
% found
% Use max value of Hough transform vs angle to find angles at which lines
% are oriented. If there is more than one major angle contribution there
% will be two peaks detected but only one peak if there is only one major
% angle contribution (ie peaks here = number of located bones = Number of
% breaks + 1)
[H,T,R] = hough(edgeImg,'RhoResolution',1,'Theta',-90:2:89.5);
maxHough = max(H, [], 1);
HoughThresh = (max(maxHough) - min(maxHough))/2 + min(maxHough);
[~, HoughPeaks] = findpeaks(maxHough,'MINPEAKHEIGHT',HoughThresh, 'MinPeakDistance', MinHoughPeakDistance);
% Plot Hough detection results
figure(1)
plot(T, maxHough);
hold on
plot([min(T) max(T)], [HoughThresh, HoughThresh], 'r');
plot(T(HoughPeaks), maxHough(HoughPeaks), 'rx', 'MarkerSize', 12, 'LineWidth', 2);
hold off
xlabel('Theta Value'); ylabel('Max Hough Transform');
legend({'Max Hough Transform', 'Hough Peak Threshold', 'Detected Peak'});
% Locate site of break
if numel(HoughPeaks) > 1;
BreakStack = zeros(size(img, 1), size(img, 2), numel(HoughPeaks));
% Convolute edge image with line of detected angle from hough transform
for m = 1:numel(HoughPeaks);
boneKernel = strel('line', HoughConvolutionLength, T(HoughPeaks(m)));
kern = double(bwmorph(boneKernel.getnhood(), 'dilate', HoughConvolutionDilate));
BreakStack(:,:,m) = imfilter(edgeImg, kern).*edgeImg;
end
% Take difference between convolution images. Where this crosses zero
% (within tolerance) should be where the break is. Have to filter out
% regions elsewhere where the bone simply ends.
brImg = abs(diff(BreakStack, 1, 3)) < BreakLineTolerance*max(BreakStack(:)) & edgeImg > 0;
[BpY, BpX] = find(abs(diff(BreakStack, 1, 3)) < BreakLineTolerance*max(BreakStack(:)) & edgeImg > 0);
brImg = bwmorph(brImg, 'dilate', breakPointDilate);
brReg = regionprops(brImg, 'Area', 'MajorAxisLength', 'MinorAxisLength', ...
'Orientation', 'Centroid');
brReg(vertcat(brReg.Area) ~= max(vertcat(brReg.Area))) = [];
% Calculate bounding ellipse
brReg.EllipseCoords = zeros(100, 2);
t = linspace(0, 2*pi, 100);
brReg.EllipseCoords(:,1) = brReg.Centroid(1) + brReg.MajorAxisLength/2*cos(t - brReg.Orientation);
brReg.EllipseCoords(:,2) = brReg.Centroid(2) + brReg.MinorAxisLength/2*sin(t - brReg.Orientation);
else
brReg = [];
end
% Draw ellipse around break location
figure(2)
imshow(img)
hold on
colormap('gray')
if ~isempty(brReg)
plot(brReg.EllipseCoords(:,1), brReg.EllipseCoords(:,2), 'r');
end
hold off