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Reducing Noise Component On Medical Images

机译：减少医学图像上的噪声成分

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Medical visualization and analysis of medical data is an actual direction. Medical images are used in microbiology, genetics, roentgenology, oncology, surgery, ophthalmology, etc. Initial data processing is a major step towards obtaining a good diagnostic result. The paper considers the approach allows an image filtering with preservation of objects borders. The algorithm proposed in this paper is based on sequential data processing. At the first stage, local areas are determined, for this purpose the method of threshold processing, as well as the classical ICI algorithm, is applied. The second stage uses a method based on based on two criteria, namely, L2 norm and the first order square difference. To preserve the boundaries of objects, we will process the transition boundary and local neighborhood the filtering algorithm with a fixed-coefficient. For example, reconstructed images of CT, x-ray, and microbiological studies are shown. The test images show the effectiveness of the proposed algorithm. This shows the applicability of analysis many medical imaging applications.
机译：医学可视化和医学数据分析是一个实际的方向。医学图像用于微生物学，遗传学，放射学，肿瘤学，手术，眼科等。初始数据处理是获得良好诊断结果的重要步骤。本文认为该方法可以在保留对象边界的情况下进行图像过滤。本文提出的算法基于顺序数据处理。在第一阶段，确定局部区域，为此，应用阈值处理方法以及经典ICI算法。第二阶段使用基于两个准则的方法，即L2范数和一阶平方差。为了保留对象的边界，我们将使用固定系数处理过渡边界和局部邻域滤波算法。例如，显示了CT，X射线和微生物研究的重建图像。测试图像表明了该算法的有效性。这表明分析在许多医学成像应用中的适用性。

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