How can I detect blood vessels in retinal image?

5 Retinal Images, Analysis of Eye, etc.
5.1 Retinal Images, Angiography, Blood Vessels in the Eye
5.2 Glaucoma Retinopathy, Retinal Analysis Application
5.3 Diabetic Retinopathy, Retinal Analysis Application

We can't help you with coding up some algorithm that we don't even know what it is yet. Pick an algorithm first, then give a shot at coding it up. http://matlab.wikia.com/wiki/FAQ#Can_you_program_up_the_algorithm_in_this_article_for_me_and_explain_it_to_me.3F

Then come back here if you have syntax problems, error messages, or need help with program flow.

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Biswarup Dass 2013-11-11

在 MATLAB Online 中打开

I have got a code and the approach used for blood vessels extraction is called the Matched FIlter - First Derivative of Gaussian. There are four M files. I am facing troubles while going through the code. Here is the code

function [Z] = main()

% Main function that calls all others

% Outputs:

% Z(1,1) - true positive rate

% Z(1,2) - true negative rate

% Z(1,3) - accuracy

Z = zeros(20,3);

MaskForGDRange = zeros(605,700);

for row = 1:605

    for col = 1:700
        if (row-302)*(row-302) + (col-350)*(col-350) > 62500
            maskForGDRange(row,col) = 1;
        end
    end

end

idx = 1;

for k=[1:5 44 77 81:82 139 162:163 235:236 239 240 255 291 319 324]

k

mask_name = strcat('D:\MyD 1\stare- images\mask\im',num2str(k,'%04d'),'_mask.ppm');

mask = imread(mask_name);

mask = mask(:,:,2);

mask = logical(mask);

im_name = strcat('D:\MyD 1\stare-images\im',num2str(k,'%04d'),'.ppm');

im = imread(im_name);

se = strel('disk',2);

mask=imerode(mask,se);

im = double(im(:,:,2));

    man_name = strcat('D:\MyD 1\stare-images\labels-ah\im',num2str(k,'%04d'),'.ah.ppm');
    man = imread(man_name);
    [vess1]=MatchFilterWithGaussDerivative([],1,im,1.5,1.5,9,5,41,201,8,mask,maskForGDRange,3,40);
    [vess2]=MatchFilterWithGaussDerivative([],2,im,1,1,9,5,21,101,8,mask,maskForGDRange,2,40);

vess = vess1 | vess2;

    [tpr tnr accu] = acc(vess, mask, man);
    Z(idx,1,1) = tpr;
    Z(idx,2,1) = 1 - tnr;
    Z(idx,3,1) = accu;
    idx = idx + 1;
end
return

Biswarup Dass 2013-11-11

在 MATLAB Online 中打开

This is the function M file used

 function [vess] = MatchFilterWithGaussDerivative(k,num,im,sigmaForMF,sigmaForGD,yLengthForMF,yLengthForGD,tForMatchfilterRes,tForGaussDerRes, numOfDirections,mask,maskForGDRange,c_value,t)

% Retinal vessel extraction by matched filter with

% first-order derivative of Gaussian

% Inputs:

% k - ignore, used for testing purposes only

% num - image number

% im - input image

% sigmaForMF - scale value of MF

% sigmaForGD - scale value of FDOG

% yLengthForMF - length of neighborhood along y-axis of MF

% yLengthForGD - length of neighborhood along y-axis of FDOG

% tForMatchfilterRes - threshold value of MF

% tForGaussDerRes - threshold value of FDOG

% numOfDirections - number of orientations

% mask - image mask

% maskForGDRange - another image mask

% c_value - c value

% t - threshold value of MF-FDOG

%

% Output:

% vess - vessels extracted

if isa(im,'double')~=1

im = double(im);

end

[rows,cols] = size(im);

MatchFilterRes(rows,cols,numOfDirections) = 0;

GaussDerivativeRes(rows,cols,numOfDirections) = 0;

K2=tForMatchfilterRes;

S2=ones(K2,K2)/(K2^2);

for i = 0:numOfDirections-1

matchFilterKernel =

MatchFilterAndGaussDerKernel(sigmaForMF,yLengthForMF, pi/numOfDirections*i,0);

    gaussDerivativeFilterKernel = 
MatchFilterAndGaussDerKernel(sigmaForGD,yLengthForGD, 
pi/numOfDirections*i,1);
    MatchFilterRes(:,:,i+1) = conv2(im,matchFilterKernel,'same');
    RDF = conv2(im,gaussDerivativeFilterKernel,'same');
    GaussDerivativeRes(:,:,i+1) = abs(conv2(RDF,S2,'same'));

end

[maxMatchFilterRes] = max(MatchFilterRes,[],3);

accoGaussDerivativeRes = min(GaussDerivativeRes,[],3);

averageGD = conv2(accoGaussDerivativeRes,S2,'same');

meanGD = mean(mean(averageGD));

normalGD = averageGD / meanGD;

big = normalGD >= 5;

small = normalGD < 5;

W = c_value + normalGD / 2;

W = W .* ~maskForGDRange;

W = W + maskForGDRange * c_value;

K1 = tForGaussDerRes;

S1=ones(K1,K1)/(K1^2);

averageMF = conv2(maxMatchFilterRes,S1,'same');

vess = (maxMatchFilterRes - W.*averageMF)>0;

vess = vess & mask;

se = strel('square',3);

vess = imclose(vess,se);

vess = bwmorph(vess,'close');

[L num] = bwlabel(vess, 8);

prop = regionprops(L, 'Area');

idx = find([prop.Area] > t);

vess = ismember(L,idx);

arun anoop m 2020-8-31

My MATLAB R2020a trial version expired. Can you renew that trial version for 3/6 months??

Image Analyst 2020-8-31

I don't know what "yarn based feature extraction" is, or if it will work on blood vessels. Give it a try.

If you want to use MATLAB for another 3 to 6 months beyond the original one month, then you'll have to buy a version. You can't just keep using it forever and getting free extensions. You realize that the people who write MATLAB for you deserve to get a paycheck just like you, right?

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Answer 3

Priya Natarajan 2013-12-11

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/105145-how-can-i-detect-blood-vessels-in-retinal-image#answer_118055

Zhang.pdf

Hi Biswarup... this is a code for retinal vessel segmentation with Matched filter and first derivative of gaussian filter.

I have attached the supporting paper for the code... refer that for explanation

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harjatin baweja 2016-4-28

Where is the code for this paper ?

Image Analyst 2016-4-29

It would be with the authors. Generally code is not submitted as a separate file along with the article, unless it's actually part of the article itself.

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