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3D CT to 2D low dose single-plane fluoroscopy registration algorithm for in-vivo knee motion analysis

机译:从3D CT到2D低剂量单平面荧光检查的配准算法,用于体内膝关节运动分析

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A limitation to accurate automatic tracking of knee motion is the noise and blurring present in low dose X-ray fluoroscopy images. For more accurate tracking, this noise should be reduced while preserving anatomical structures such as bone. Noise in low dose X-ray images is generated from different sources, however quantum noise is by far the most dominant. In this paper we present an accurate multi-modal image registration algorithm which successfully registers 3D CT to 2D single plane low dose noisy and blurred fluoroscopy images that are captured for healthy knees. The proposed algorithm uses a new registration framework including a filtering method to reduce the noise and blurring effect in fluoroscopy images. Our experimental results show that the extra pre-filtering step included in the proposed approach maintains higher accuracy and repeatability for in vivo knee joint motion analysis.
机译:精确自动跟踪膝盖运动的局限性在于低剂量X射线荧光透视图像中存在的噪声和模糊。为了更精确地跟踪,应在保留骨骼等解剖结构的同时减少此噪声。低剂量X射线图像中的噪声是从不同来源生成的,但是,迄今为止,量子噪声是最主要的噪声。在本文中,我们提出了一种精确的多模式图像配准算法,该算法成功将3D CT注册到为健康膝盖捕获的2D单平面低剂量噪声和模糊荧光透视图像。所提出的算法使用了一种新的配准框架,其中包括一种滤波方法,以减少荧光透视图像中的噪声和模糊效果。我们的实验结果表明,所提出的方法中包括的额外预过滤步骤可为体内膝关节运动分析保持更高的准确性和可重复性。

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