In this paper, we present non-identical unsupervised clustering techniques for the segmentation of CT brain images. Prior to segmentation, we enhance the visualization of the original image. Generally, for the presence of abnormal regions in the brain images, we partition them into 3 segments, which are the abnormal regions itself, the cerebrospinal fluid (CSF) and the brain matter. However, for the absence of abnormal regions in the brain images, the final segmented regions will consist of CSF and brain matter only. Therefore, our system is divided into two stages of clustering. The initial clustering technique is for the detection of the abnormal regions. The later clustering technique is for the segmentation of the CSF and brain matter. The system has been tested with a number of real CT head images and has achieved satisfactory results.

中文翻译：

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使用无监督聚类分割 CT 脑图像

在本文中，我们提出了用于分割 CT 脑图像的非相同无监督聚类技术。在分割之前，我们增强了原始图像的可视化。通常，对于大脑图像中存在异常区域，我们将它们划分为 3 个部分，即异常区域本身、脑脊液 (CSF) 和脑物质。然而，由于大脑图像中没有异常区域，最终分割的区域将仅由脑脊液和脑物质组成。因此，我们的系统分为两个聚类阶段。最初的聚类技术是为了检测异常区域。后面的聚类技术是用于 CSF 和脑物质的分割。该系统已经通过多张真实的头部CT图像进行测试，取得了满意的效果。