can someone teach me how to find optic disc using three channels (RGB) ,shannon information content per channel in the ROI, OD centre using the circular Hough transform

i need help with the algorithm that should , automatically: (i) uses the three channels (RGB) of the digital colour image to locate the region of interest (ROI) where the OD lies, (ii) measures the Shannon information content per channel in the ROI, to decide which channel is most appropriate for searching for the OD centre using the circular Hough transform

Answer 1

[Image Analyst]

Are you talking about color channel? The blue channel should have the greatest contrast between the retina and the optic disc.

What is your formula for Shannon's information content?

Optic discs are not perfectly circular so I don't know why you want to use hough to assume it's circular instead of just thresholding or using one of the more sophisticated published methods :

• 20.5 Retinal Images, Analysis of Eye, etc.
• 20.5.1 Eye, Cornea, Corneal Images
• 20.5.2 Optic Disc Location, Optic Disc Detection
• 20.5.3 Retinal Images, Angiography, Blood Vessels in the Eye
• 20.5.3.1 Retinal Microaneurysms, Detection
• 20.5.4 Glaucoma Retinopathy, Retinal Analysis Application
• 20.5.5 Cataracts, Detection, Analysis, Surgery
• 20.5.6 Diabetic Retinopathy, Retinal Analysis Application
• 20.5.7 Macular Degeneration Detection, AMD, Retinal Analysis Application
• 20.5.8 Retinal Images, Optical Coherence Tomography, OCT

In short, you might be able to do (in the simplest possible case but not typical case):

mask = rgbImage(:,:,3) > someThreshold;
mask = bwareafilt(mask, 1); % Take largest blob.  Assumes disc is not cut into multiple parts by blood vessels.
% Find Centroid.
props = regionprops(mask, 'Centroid');
xyCenter = props.Centroid
hold on;
plot(xyCenter(1), xyCenter(2), 'b+', 'MarkerSize', 250); % Plot blue crosshairs at centroid.