The study of pre-processing method of brain vessel segmentation based on parameterized statistical model
Xingce Wang, Feng Hua Xu, Leng Chang, Mingquan Zhou, Zhongke Wu, Liu Xin-yu · 2010
For the 3D brain MRI parameterized statistical model segmentation method, the pre-processing method of brain image is brought forward for the model. First the DWM(directional weighted median) filter and Gaussian template are used to de-noise the brain MRI image. Then the Laplacian operator is used to sharpen the image, and the Robert operator is used to realize the edge detection, which can improve the measurement accuracy. And the MIP (maximum intensity projection) algorithm is applied to extract the largest connected component. The image of only brain vessel and part brain tissue can be obtained and the influence of background and no brain vessels like tissue to the images is eliminate. After pre-processing stage, the brain image is analyzed as the input to the parameterized statistical model. The small branches of the brain vessel can be segmented.