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Local Orientation-Dependent Noise Propagation for Anisotropic Denoising of CT-Images

机译:局部取向依赖性噪声传播,用于CT图像的各向异性去噪

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In X-ray Computed Tomography (CT) the measured projections and consequently the reconstructed CT images are subject to quantum and electronics noise. While noise in the projections can be well described and estimated with a corresponding physics model, the distribution of noise in the reconstructed CT images is not directly evident. Due to attenuation variations along different directions, the nature of noise in CT images is non-stationary and non-isotropic. This complicates the direct application of standard post-processing methods like bilateral filtering. In this article we describe a possibility to compute precise orientation dependent noise estimates for every pixel position. This is done by analytic propagation of projection noise estimates through indirect fan-beam filtered backprojection reconstruction. The resulting orientation dependent image noise estimates are subsequently used in adaptive bilateral filters. Taking into account the non-stationary and non-isotropic nature of noise in CT images, a reduction in image noise of about 55% compared to 39% of the standard approach is achieved with much less variability over different image regions.
机译:在X射线计算机断层扫描(CT)中,测量的投影并因此将重建的CT图像受到量子和电子噪声。虽然噪声在投影中可以很好地描述并用相应的物理模型估计,但重建的CT图像中的噪声分布不直接明显。由于沿不同方向的衰减变化,CT图像中噪声的性质是非静止和非各向同性的。这使得标准后处理方法的直接应用相反,如双侧过滤。在本文中,我们描述了计算每个像素位置的精确取向依赖性噪声估计的可能性。这是通过间接扇形波束滤波反射重构的分析噪声估计的分析传播来完成的。随后在自适应双边滤波器中使用得到的取向相关图像噪声估计。考虑到CT图像中噪声的非静止和非各向同性性质,与39%的标准方法相比,图像噪声的降低率为39%,在不同的图像区域的可变异程度下降得多。

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