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How to measure the curvature of object boundary?

Asked by sana3 sal on 20 Jun 2018
Latest activity Commented on by sana3 sal on 22 Dec 2018
Hello, I have tried the solution : https://www.mathworks.com/matlabcentral/answers/164349-how-to-calculate-the-curvature-of-a-boundaries-in-binary-images and i tried it on my image. it works, but i have to analyse the curvature. let's be clear, the first photo attached is representation for normal case of some inter-vertebrae discs. the second is abnormal case, where we can notice the disc bulge makes the curve. now in order to classify each one, we need to look at the curve in the upper part of the object, so that it will classify them automatically based on this. How i can represent this curve mathematically in order to make this automatic classification? or what does the plot means in my cases?
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  5 Comments

My problem with this solution: https://www.mathworks.com/matlabcentral/fileexchange/32696-2d-line-curvature-and-normals that i don't know how to extract the Vertices,Lines from my images!
You just made an edit. Is there anything there that is different from last June? We don't know, so we're assuming no change since June, since you didn't say.
I deleted the part that is related to my thesis

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1 Answer

Answer by Anton Semechko on 21 Jun 2018
 Accepted Answer

Thanks for the clarification. If I understand correctly, the features you seek should be extracted from an open-curve that represents dorsal portion of the interververtebral disk space. In this regard, I can think of a couple curvature-based features that can be used to discriminate between 'normal' and 'abnormal' cases. The first, and simplest, feature would be mean curvature of the curve (obtained by integrating curvature along the curve and dividing by the total arc length). When using this feature, one would expect that pathological cases would have higher mean curvature. Second feature would be a histogram of curvatures. This is a generalization of the first feature. One would expect that histograms of pathological samples would have thicker tails and modes shifted to the right. In any case, going forward, it would helpful if you posted some training data on here, so that I, and other people on here have something to work with.

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So what accuracy or quality do you expecting the data to be? those the attached are the original images before threshold binarization.
I think you are more knowledgeable in terms of anatomy. So I am not disputing the fact that the segmentations are correct. What I am saying, is that in view of the data, it will not be possible to extract anatomically consistent boundary profiles across subjects. Hence, using curvature-based features for this type of data is a bad idea.
I understand you, thank you for your guidance.

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