自适应区域生长算法在医学图像分割中的应用
Adaptive Region Growing Algorithm in Medical Images Segmentation
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摘要: 提出一种通过计算种子点附近邻域统计信息,自适应改变生长标准参数用于医学图像分割的算法.在切片图像预处理过程中,考虑到体数据相邻切片之间高度的相关性,在相邻层之间采取高斯核滤波去除噪声,并通过各向异性滤波算法对该层切片进行滤波.实验结果表明,该算法可有效地提取出图像区域,具有较好的鲁棒性.Abstract: In this paper we put forward an adaptive region growing algorithm for image segmentation by estimating the parameters through investigation of the statistical characteristics in local regions. By the algorithm, we use Gaussian mixture model to describe the properties of the region and employ an effective data clustering algorithm to calculate the parameters. Considering the similarity of the neighbor slices in the medical volume data, a Gaussian filter is applied in perpendicular direction to reduce the noise. In a slice image, an anisotropic diffusion filter is used to preserve the edge information. A number of medical images are tested to demonstrate the applicability and reliability of the proposed algorithm.
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