摘要
本文提出一种基于图像灰度值的K-均值聚类算法,并利用这种算法对脑部核磁图像分割进行测试。K-均值聚类算法是一种自动数据分类的方法,该类算法仅依据图像像素点的灰度值将其分为不同的点群。我们使用这种图像分割算法,在针对脑部核磁图像的分割中得到了理想的分割结果,可以清晰地看到白质,灰质,皮质,第三脑室及背景的分割结果。
the paper presents a k-means algorithm based on image grey level,and test the brain's MR image segmentation by this algorithm.The gray value of the pixels in the image gives the consistent property with the cluster-center pixels.The multi-regions in a image can be merged together according to the gray value.The application of this algorithm on MR image segmentation is successful.The results showed white matter,grey matter,the cortex,the ventricles of the brain and the background.
出处
《医疗装备》
2012年第1期13-16,共4页
Medical Equipment
关键词
磁共振图像
图像分割
K-均值算法
Magnetic resonance imaging
Image segmentation
K-means algorithm