Effect of Smoothing on Sparsity Prior CT Reconstruction

Sajib Saha, M. Tahtali, A. Lambert, M. Pickering
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引用次数: 2

Abstract

We systematically evaluate the performance of smoothing on several state-of-the-art sparsity prior CT reconstruction algorithms. State-of-the-art algorithms have been implemented and their performance analyzed with and without applying different smoothing filters. Aiming for successful reconstruction from less number of projections, sparsity prior reconstruction algorithms are found to be useful in CT, provided that the signal reconstruction is performed in a compressed domain (i.e. gradient or wavelet domain). The subject matter of this work is the investigation of the reconstruction performance variation with the application of a smoothing filter prior sparsifying transform. Experiments on simulated and real medical images show that the performance of the reconstruction algorithms vary, and smoothing before the sparsifying transform ensures better reconstruction.
平滑对稀疏度先验CT重建的影响
我们系统地评估了几种最先进的稀疏性先验CT重建算法的平滑性能。最先进的算法已经实现,并在使用和不使用不同的平滑滤波器的情况下分析了它们的性能。为了从更少的投影中成功重建,稀疏先验重建算法在CT中是有用的,前提是在压缩域(即梯度域或小波域)中进行信号重建。本工作的主题是研究应用平滑滤波先验稀疏化变换后重建性能的变化。在模拟和真实医学图像上的实验表明,重建算法的性能各不相同,在稀疏化变换之前进行平滑可以保证更好的重建。
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