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GUIDEWIRE TRACKING USING A NOVEL SEQUENTIAL SEGMENT OPTIMIZATION METHOD IN INTERVENTIONAL X-RAY VIDEOS

机译:使用新型序贯段优化方法在介入X射线视频中导丝跟踪

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Robust guidewire tracking is important in many clinical applications yet it is still a very challenging problem. A guidewire is a thin, deformable medical device and usually appears in low quality X-ray imagery. Moreover, distracters with stronger gradient response may also present in the scenario. In this paper, we model the wire-like structure as a sequence of small segments and formulate guidewire tracking as a graph-based optimization problem which aims to find the optimal link set. To overcome distracters, we extract them from the dominant motion pattern and propose a confidence re-weighting process in the appearance measurement. Medical validations have shown over 50 percent reduction in mean tracking error in 54 clinical X-Ray sequences compared with a state-of-the-art guidewire tracking method.
机译:强大的导丝跟踪在许多临床应用中都很重要,但它仍然是一个非常具有挑战性的问题。导丝是一种薄,可变形的医疗装置,通常出现在低质量的X射线图像中。此外,场景中还可以存在具有更强梯度响应的干扰因素。在本文中,我们将线状结构模拟作为小段的序列,并将导丝跟踪制定为基于图的优化问题,旨在找到最佳链接集。为了克服干扰因素,我们从主导运动模式中提取它们,并提出了在外观测量中的置信度重量过程。与最先进的导丝跟踪方法相比,医学验证在54临床X射线序列中的平均跟踪误差减少了50%以上。

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