基于Gabor滤波的头部CT图像分割算法
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引用本文:曲蕴慧1?覮,弓明2,廖尹坤2,王鑫2,扬伍连2 ,刘哲2.基于Gabor滤波的头部CT图像分割算法[J].计算技术与自动化,2019,(1):157-159
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曲蕴慧1?覮,弓明2,廖尹坤2,王鑫2,扬伍连2 ,刘哲2 (1.西安医学院 计算机教研室陕西 西安7100212.西安医学院 医学技术系陕西 西安 710021) 
中文摘要:针对传统图像分割算法在头部CT图像分割时存在的易受光线、伪影等噪声干扰等问题,提出一种基于Gabor滤波的头部CT图像分割算法。首先使用Gabor滤波器对头部CT图像进行滤波,虑除图像中的光线以及伪影等噪声,然后使用Gaussian滤波器对图像进行平滑操作,最后使用二阶微分算子:Laplacian边缘检测算子对图像进行分割处理。实验结果表明:提出的基于Gabor滤波的头部CT图像分割算法能够有效的分割出头部CT图像边缘,并对头部CT图像中常见噪声伪影,具有很强的鲁棒性。
中文关键词:Gabor滤波器  Gaussian滤波器  边缘检测  头部CT图像
 
Head CT Images Segmentation Algorithm Based on Gabor Filter
Abstract:Traditional image segmentation algorithms have the problem of being susceptible to noise interference in head CT image segmentation. Considering these problems,a head CT image segmentation algorithm based on Gabor filter is proposed. Firstly,Gabor filter is used to filter out artifacts and noise points in head CT images. Then the Gaussian filter is used to smooth the image after Gabor filter. Finally,the two order differential operator: Laplacian edge detector is used to segment the image. Experimental results show that the algorithm proposed in this paper can effectively divide the edge of the head CT image,and has strong robustness to the common noise artifacts in the head CT image
keywords:Gabor filter  Gaussian filter  edge detection  head CT images
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