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3D Active Vessel Tracking Using an Elliptical Prior

机译:使用椭圆先验的3D主动血管跟踪

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In this paper, we propose a novel vessel tracking method, called active vessel tracking (AVT). The proposed method retains the major advantages that most 2D segmentation methods have demonstrated for 3D tracking while overcoming the drawbacks of previous 3D vessel tracking methods. Under the assumption that the vessel is cylindrical, thereby making its cross-section elliptical, the AVT finds a plane perpendicular to the vessel axis while tracking the vessel along its length. Also, We propose a method for vessel branch detection to automatically track complete vascular networks from a single starting point, whereas the previously proposed solutions have usually been limited in handling vessel bifurcations precisely on 3D or have required considerable user interaction. Our results show that the method is robust and accurate in both synthetic and clinical cases. In an experiment on synthetic data sets, the proposed method achieved a tracking accuracy of 96.1±0.5, detecting 99.1% of the branches. In an experiment on abdominal CTA data sets, it achieved a tracking accuracy of 98.4±0.5 for six target vessels, detecting 98.3% of the branches. These results show that the proposed method can outperform previous methods for vessel tracking.
机译:在本文中,我们提出了一种新颖的血管跟踪方法,称为主动血管跟踪(AVT)。所提出的方法保留了大多数2D分割方法已证明用于3D跟踪的主要优点,同时克服了先前3D血管跟踪方法的缺点。在假定容器为圆柱形,从而使其横截面为椭圆形的前提下,AVT在沿其长度跟踪容器的同时找到了垂直于容器轴线的平面。同样,我们提出了一种用于血管分支检测的方法,该方法可以从单个起点自动跟踪完整的血管网络,而先前提出的解决方案通常在精确地以3D方式处理血管分叉方面受到限制,或者需要大量的用户交互作用。我们的结果表明,该方法在合成和临床病例中均可靠且准确。在合成数据集的实验中,提出的方法实现了96.1±0.5的跟踪精度,检测到99.1%的分支。在腹部CTA数据集上的实验中,它对六个目标血管的跟踪精度为98.4±0.5,检测到98.3%的分支。这些结果表明,所提出的方法可以胜过以前的船只跟踪方法。

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