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Fully automated segmentation of MRI brain image using mixture Gaussian model and three-dimensional morphological filter

机译:使用混合高斯模型和三维形态学滤波器对MRI脑图像进行全自动分割

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The method to segment a human brain of a magnetic resonance image is proposed in which tissue characteristic and structure are considered using two algorithms, one is mixture Gaussian model and the other is three-dimensional morphological filter. First, the image is segmented into five clusters of background, cerebro-spinal fluid, gray matter, white matter and others by mixture Gaussian model applied to a histogram of voxel values. Next, a three-dimensional morphological filter is invoked to modify misclustered voxels. All of steps can be done in automatically. The brain structures are segmented well in derived results and the proposed algorithm has a potential possibility for clinical applications.
机译:提出了一种对人脑磁共振图像进行分割的方法,该方法使用两种算法考虑组织的特征和结构,一种是混合高斯模型,另一种是三维形态滤波器。首先,通过将混合高斯模型应用于体素值的直方图,将图像分为背景,脑脊髓液,灰质,白质和其他五类。接下来,调用三维形态过滤器以修改聚类错误的体素。所有步骤都可以自动完成。大脑结构在得到的结果中被很好地分割,并且所提出的算法具有临床应用的潜在可能性。

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