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Preprocessing of Radiological Images; Comparison of the Application of Polynomic Algorithms and Artificial Neural Networks to the Elimination of Variations in Background Luminosity

机译:放射图像的预处理;多项式算法和人工神经网络在消除背景光度变化中的应用比较

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摘要

One of the major difficulties arising in the analysis of a radiological image is that of non-uniform variations in luminosity in the background. This problem urgently requires a solution given that differing areas of the image have attributed to them the same values and this may potentially lead to grave errors in the analysis of an image. This article describes the application of two different methods for the solution of this problem: polynomial algorithms and artificial neural networks. The results obtained using each method are described and compared, the advantages and drawbacks of each method are commented on and reference is made to areas of potential interest from the point of view of future research.
机译:放射图像分析中出现的主要困难之一是背景中光度的不均匀变化。鉴于图像的不同区域赋予它们相同的值,因此这个问题迫切需要一种解决方案,这可能会导致图像分析中的严重错误。本文介绍了解决此问题的两种不同方法的应用:多项式算法和人工神经网络。描述并比较了使用每种方法获得的结果,评述了每种方法的优缺点,并从将来的研究角度参考了可能感兴趣的领域。

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