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A novel intensity limiting approach to Metal Artefact Reduction in 3D CT baggage imagery

机译:减少3D CT行李图像中金属伪影的强度限制新方法

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This paper introduces a novel technique for Metal Artefact Reduction (MAR) in the previously unconsidered context 3D CT baggage imagery. The output of a conventional sinogram completion-based MAR approach is refined by imposing an upper limit on the intensity of the corrected images and by performing post-filtering using the non-local means filter. Furthermore, performance is evaluated using a novel quantitative analysis technique, using the ratio of noisy 3D SIFT detection points identified, as well as a standard qualitative comparison (visual quality). The objective of the quantitative analysis is to evaluate the impact of MAR on the application of computer vision techniques for automatic object recognition. The study yields encouraging results in both the qualitative and quantitative analyses. The proposed method yields a significant improvement in performance when compared to algorithms based on linear interpolation and reprojection-reconstruction; especially in terms of reducing the occurrence of new artefacts in the corrected images. The results serve as a strong indication that MAR will aid human and computerised analyses of 3D CT baggage imagery for transport security screening.
机译:本文介绍了一种在以前未考虑的上下文3D CT行李图像中用于减少金属伪影(MAR)的新技术。通过对校正图像的强度施加上限并使用非局部均值滤波器执行后滤波,可以改进常规基于正弦图完成的MAR方法的输出。此外,使用新颖的定量分析技术,使用识别出的嘈杂3D SIFT检测点的比率以及标准的定性比较(视觉质量)来评估性能。定量分析的目的是评估MAR对应用计算机视觉技术进行自动对象识别的影响。该研究在定性和定量分析中均得出令人鼓舞的结果。与基于线性插值和重投影重构的算法相比,该方法在性能上有显着提高。特别是在减少校正图像中出现新伪像方面。该结果有力地表明,MAR将协助对3D CT行李图像进行人为和计算机分析,以进行运输安全检查。

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