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How can I segment micro aneurysms and hemorrhages from fundus images in case of diabetic retinopathy based on thresholding?Please suggest me threshold to segment this.Thanks in advance
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In this image the dark lesions has to be segmented only which excludes retinal blood vessels .
4 Comments
KALYAN ACHARJYA
on 14 Mar 2018
What is your question exactly (specific)?
For both (microaneurysms and hemorrhages), you have to go for the different classifier.
supriya suman
on 14 Mar 2018
Yes sir,I have to detect microaneurysms and hemorrahages both from the image.I am using adaptive threshold but along with microaneurysms and hemorrahages,I am getting blood vessels which is not required.Is there any thresholding method to detect microaneurysms and hemorrahages.Thanks
Star Strider
on 14 Mar 2018
There aren’t any microaneurysms in that image. There are only hemorrhages and exudates (infarcts).
supriya suman
on 15 Mar 2018
Yes,but it can be present in other image.Basically I want to segment both
Answers (1)
Image Analyst
on 14 Mar 2018
Thresholding alone is most likely no good unless there is substantial pre- and post-processing.
binaryImage = rgbImage(:,:,3) < someValue;
18 Comments
supriya suman
on 14 Mar 2018
yes sir, u are right but I want some easy code,as I am beginner in this field.
supriya suman
on 14 Mar 2018
Can anyone provide top-hat transform code to supress the blood vessels for accurate detection ?
Image Analyst
on 15 Mar 2018
There is an example in the help for imtophat(). Chances are it won't be that great. At the very least you'd have to post process the result to clean it up and remove false positives.
supriya suman
on 15 Mar 2018
I am getting image like this after applying thresholding but I don't want vessels here.Please suggest me some method to suppress blood vessels.
Image Analyst
on 15 Mar 2018
I already did a suggestion. In my answer, I said this:
Personally I have not reviewed all those methods and don't know the "best" one. I imagine all the authors think theirs is the best. Nor do I have any code to do them. Perhaps you can look for an overview/survey paper.
Image Analyst
on 16 Mar 2018
What is your definition of eliminate? Blacken? Just make a 3-D mask with repmat() or cat(),
mask3d = cat(3, mask, mask, mask);
and use the mask as an index to blacken those pixels.
rgbImage(mask3d) = 0;
supriya suman
on 16 Mar 2018
I want to substract blood vessles from the image using line operator But i know how to do it.
Image Analyst
on 16 Mar 2018
Subtracting the vessel image pixel values from the original image is the same as blackening the pixels. The value will be zero there.
Image Analyst
on 16 Mar 2018
I don't know what that means. "through" the mask??? You've already recognized the vessels - that's how you created the mask in the first place. Right? How did you get the mask if it was not from finding/recognizing the vessels?
supriya suman
on 16 Mar 2018
No,i have not recognized vessels.I need code to detect blood vessels to eliminate them after subtracting from image .
Image Analyst
on 16 Mar 2018
I still don't understand. You say you want to eliminate them "AFTER" subtracting them from the image. So to subtract them, you must have identified them already, right? If you're already subtracted them, then you must have a mask for them. And if they've already been subtracted, what does the image look like now? What is there that is left to "eliminate" AFTER subtraction has been done? After subtraction, the pixels will be black where the vessels are. So what does "eliminate" mean to you? You want to eliminate the black (subtracted) pixels??? Do you want to use regionfill() to fill in the black/subtracted areas with local background?
Image Analyst
on 17 Mar 2018
I already gave my answer for that above. Perhaps you overlooked it so here it is again:
So pick one and code it up. Or ask the authors if you can get (free or buy) their code. But I don't have the code myself.
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