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Contextual Filtering of CT Images Using Markovian Wiener Filters with a Non Local Means Approach for Statistical Estimation

机译:使用非局部均值方法的马尔可夫维纳滤波器对CT图像进行上下文过滤以进行统计估计

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摘要

Recently, investigations on medical imaging have been indicating a strong correlation between cases of cancers and the increasing number of Computed Tomography (CT) exams, mainly due to high radiation doses to which patients are exposed during the data acquisition process. Thus, there is a need to reduce the radiation doses whereas still keeping satisfactory quality images for diagnosis. In this paper, we propose to filter noise in CT images using contextual versions of Wiener Filter such as Generalized Wiener Filter (GWF) and Non Local Means approach for parameter estimation. Experiments show that the proposed methods are promising, since they provide good results with no significant increase in the computational cost.
机译:最近,对医学成像的研究表明,癌症病例与计算机断层扫描(CT)检查数量的增加之间存在很强的相关性,这主要是由于在数据采集过程中患者受到的辐射剂量很高。因此,需要减少辐射剂量,同时仍保持令人满意的质量图像用于诊断。在本文中,我们建议使用上下文版本的Wiener滤波器(例如通用Wiener滤波器(GWF)和非局部均值方法)对CT图像中的噪声进行参数估计。实验表明,所提出的方法是有希望的,因为它们提供了良好的结果,并且没有显着增加计算成本。

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