Blood Vessels recognition in retinal image

Have methods like the application of contrast colour optical filters to enhance contrast been tried?

I used this code:
imm_temp=double(f_analyzed); m=min(imm_temp😀));
M=max(imm_temp😀));
betcontr_imm=255*(imm_temp-m)/(M-m);
betcontr_imm=uint8(betcontr_imm);
betcontr_immlog=mat2gray(log(1 + double(f_analyzed)));

I used two type of way to improve the contrast but the better solution is the logarithmic one.

the smile is colon...

the situation is this; i have a retinal image of the blood vessels and the seg structure with all the crossover and the bifurcations. I have to create an automatic algorithm that analyzes all the cross.. and bifurc... that improves the result of the tracking algorithm that gave me the seg structure with all the coordinates of the bifurc and crossover. I read a lot of papers but i don't understand how to proceed and what type of algorithm is best for my work.
To solve my problem i take all the single big and cross and analyze them alone, so i improve the contrast and use the Laplacian and logarithmic filters with this windows
w4=fspecial('laplacian',0);
w8=[1 1 1; 1 -8 1; 1 1 1];
wlog=fspecial('log');
The best solution i can see is the w8 but it depends in particular by the image that i'm analyzing.