【图像增强】基于Frangi滤波器实现血管图像增强附matlab代码

针对眼底视网膜图像对比度低,受病变区域边界干扰,很难正确提取血管细节的问题提出了一种基于Frangi滤波器的视网膜血管分割的方法,仿真结果表明上述方法对细小血管的提取表现出良好的效果,具备很强的实用价值.

​​function [Dxx,Dxy,Dyy] = Hessian2D(I,Sigma)
% This function Hessian2 Filters the image with 2nd derivatives of a
% Gaussian with parameter Sigma.
%
% [Dxx,Dxy,Dyy] = Hessian2(I,Sigma);
%
% inputs,
% I : The image, class preferable double or single
% Sigma : The sigma of the gaussian kernel used
%
% outputs,
% Dxx, Dxy, Dyy: The 2nd derivatives
%
% example,
% I = im2double(imread('moon.tif'));
% [Dxx,Dxy,Dyy] = Hessian2(I,2);
% figure, imshow(Dxx,[]);
%
% Function is written by D.Kroon University of Twente (June 2009)​​

​​if nargin < 2, Sigma = 1; end​​

​​% Make kernel coordinates
[X,Y] = ndgrid(-round(3*Sigma):round(3*Sigma));​​

​​% Build the gaussian 2nd derivatives filters
DGaussxx = 1/(2*pi*Sigma^4) * (X.^2/Sigma^2 - 1) .* exp(-(X.^2 + Y.^2)/(2*Sigma^2));
DGaussxy = 1/(2*pi*Sigma^6) * (X .* Y) .* exp(-(X.^2 + Y.^2)/(2*Sigma^2));
DGaussyy = DGaussxx';​​

​​Dxx = imfilter(I,DGaussxx,'conv');
Dxy = imfilter(I,DGaussxy,'conv');
Dyy = imfilter(I,DGaussyy,'conv');​​

编辑

[1]袁盼, 陈以. 基于多尺度Frangi滤波器的视网膜血管分割[J]. 现代信息科技, 2020.

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