脑部磁共振成像肿瘤分割方法（MATLAB 2018）

近年脑肿瘤发病率呈上升趋势，约占全身肿瘤的5%，占儿童肿瘤的70%。CT、MRI等多种影像检查方法可用于检测脑肿瘤，其中MRI应用于脑肿瘤成像效果最佳。精准的脑肿瘤分割是病情诊断、手术规划及后期治疗的必备条件，既往研究者对脑部肿瘤分割算法进行了深入研究，并取得了很多成果。然而脑部结构复杂，包括脑皮层、灰质、白质、胼胝体、脑脊液等组织，分割精度难以保证。目前临床使用最广泛的脑部肿瘤分割方法是模糊Ｃ均值算法和均值漂移算法。图像分割主要包括滤波和分割两部分，一般选取常用于脑部胶质瘤图像分割的非局部均值滤波、中值滤波、各向异性滤波3种滤波方法和分水岭算法、模糊C均值算法等常用的不同类型分割算法。

鉴于此，本项目采用传统的图像处理算法脑部磁共振成像肿瘤图像进行分割，运行环境为MATLAB 2018。


function diff_im = anisodiff(im, num_iter, delta_t, kappa, option)
fprintf('Removing noise\n');fprintf('Filtering Completed !!');% Convert input image to double.
im = double(im);% PDE (partial differential equation) initial condition.
diff_im = im;% Center pixel distances.
dx = 1;
dy = 1;
dd = sqrt(2);% 2D convolution masks - finite differences.
hN = [0 1 0; 0 -1 0; 0 0 0];
hS = [0 0 0; 0 -1 0; 0 1 0];
hE = [0 0 0; 0 -1 1; 0 0 0];
hW = [0 0 0; 1 -1 0; 0 0 0];
hNE = [0 0 1; 0 -1 0; 0 0 0];
hSE = [0 0 0; 0 -1 0; 0 0 1];
hSW = [0 0 0; 0 -1 0; 1 0 0];
hNW = [1 0 0; 0 -1 0; 0 0 0];% Anisotropic diffusion.
for t = 1:num_iter% Finite differences. [imfilter(.,.,'conv') can be replaced by conv2(.,.,'same')]nablaN = imfilter(diff_im,hN,'conv');nablaS = imfilter(diff_im,hS,'conv');   nablaW = imfilter(diff_im,hW,'conv');nablaE = imfilter(diff_im,hE,'conv');   nablaNE = imfilter(diff_im,hNE,'conv');nablaSE = imfilter(diff_im,hSE,'conv');   nablaSW = imfilter(diff_im,hSW,'conv');nablaNW = imfilter(diff_im,hNW,'conv'); % Diffusion function.if option == 1cN = exp(-(nablaN/kappa).^2);cS = exp(-(nablaS/kappa).^2);cW = exp(-(nablaW/kappa).^2);cE = exp(-(nablaE/kappa).^2);cNE = exp(-(nablaNE/kappa).^2);cSE = exp(-(nablaSE/kappa).^2);cSW = exp(-(nablaSW/kappa).^2);cNW = exp(-(nablaNW/kappa).^2);elseif option == 2cN = 1./(1 + (nablaN/kappa).^2);cS = 1./(1 + (nablaS/kappa).^2);cW = 1./(1 + (nablaW/kappa).^2);cE = 1./(1 + (nablaE/kappa).^2);cNE = 1./(1 + (nablaNE/kappa).^2);cSE = 1./(1 + (nablaSE/kappa).^2);cSW = 1./(1 + (nablaSW/kappa).^2);cNW = 1./(1 + (nablaNW/kappa).^2);end% Discrete PDE solution.diff_im = diff_im + ...delta_t*(...(1/(dy^2))*cN.*nablaN + (1/(dy^2))*cS.*nablaS + ...(1/(dx^2))*cW.*nablaW + (1/(dx^2))*cE.*nablaE + ...(1/(dd^2))*cNE.*nablaNE + (1/(dd^2))*cSE.*nablaSE + ...(1/(dd^2))*cSW.*nablaSW + (1/(dd^2))*cNW.*nablaNW );完整代码：https://mbd.pub/o/bread/mbd-ZJacmJ9s        
end