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VOIDD: Automatic Vessel-of-Intervention Dynamic Detection in PCI Procedures

机译:Voidd:PCI程序中的自动血管动态检测

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In this article, we present the work towards improving the overall workflow of the Percutaneous Coronary Interventions (PCI) procedures by capacitating the imaging instruments to precisely monitor the steps of the procedure. In the long term, such capabilities can be used to optimize the image acquisition to reduce the amount of dose or contrast media employed during the procedure. We present the automatic VOIDD algorithm to detect the vessel of intervention which is going to be treated during the procedure by combining information from the vessel image with contrast agent injection and images acquired during guidewire tip navigation. Due to the robust guidewire tip segmentation method, this algorithm is also able to automatically detect the sequence corresponding to guidewire navigation. We present an evaluation methodology which characterizes the correctness of the guide wire tip detection and correct identification of the vessel navigated during the procedure. On a dataset of 2213 images from 8 sequences of 4 patients, VOIDD identifies vessel-of-intervention with accuracy in the range of 88% or above and absence of tip with accuracy in range of 98% or above depending on the test case.
机译:在这篇文章中,我们提出对由该获能成像仪器精确监测过程的步骤提高了经皮冠状动脉介入(PCI)程序的整体工作流程的工作。从长远来看,这种能力可以用于优化图像采集,以减少在操作过程中所采用的剂量或造影剂的量。我们目前的自动VOIDD算法来检测干预,其将被通过从与造影剂注射和导丝尖端导航期间获取的图像的血管图像的合成信息的过程中处理过的容器中。由于鲁棒导丝尖端分割方法,该算法还能够自动检测对应于导丝导航序列。我们提出了一种评价方法表征导丝尖检测和在手术过程中驾驶的容器的正确的识别的正确性。上2213个的图像从4例8组的序列的数据集,VOIDD识别血管的干预具有在88%的范围内或以上的精度和不存在与在98%的范围内或根据测试情况下以上精度尖端。

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