基于亮度阈值自适应选择的CT图像三维SUSAN滤波

2021 56th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST) Pub Date : 2021-06-16 DOI:10.1109/ICEST52640.2021.9483499

I. Draganov, R. Mironov

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引用次数: 1

摘要

针对计算机断层扫描(CT)图像中的加性高斯白噪声，提出了一种最小单值段同化核(SUSAN)滤波器的新应用。将原有的二维滤波实现扩展到三维，提出了亮度阈值的自适应选择方案。在大数据集的CT图像上的测试表明了该方法的适用性和优于三维高斯滤波器和平均滤波器的性能。目前对3D SUSAN滤波器的改进被认为也适用于其他类型的3D图像的滤波，如MRI、多光谱等。

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3D SUSAN Filtering of CT Images With Adaptive Selection of the Brightness Threshold

In this paper a new application of the Smallest Univalue Segment Assimilating Nucleus (SUSAN) filter is presented aimed at reducing the Additive White Gaussian Noise (AWGN) in Computed Tomography (CT) images. The original 2D implementation of the filter is extended in 3D and scheme for adaptive selection of the brightness threshold is proposed. Testing over large set of CT images reveal its applicability for the purpose and better performance than the 3D Gaussian and Average filters. The current modification of the 3D SUSAN filter is considered also applicable for filtering of other types of 3D images, such as MRI, multispectral and others.

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2021 56th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST)

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