基于 U-Net 网络和对极几何的介入导管空间形状重建方法
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TH74 TP39

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国家自然科学基金(61903041)项目资助


A spatial shape reconstruction method for interventional surgical cathetersbased on U-Net and epipolar geometry
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    摘要:

    介入手术是治疗心血管疾病的主要方式之一,现有手术主要依靠二维荧光透视图像指导医生操作,无法实现术中介入 导管的三维可视化,限制了手术效率和安全性。 面向心血管介入手术临床精准治疗的需求,提出一种基于 U-Net 网络和对极几 何的介入手术导管空间形状重建方法,实现术中介入手术导管三维形状的重建。 首先利用 U-Net 网络分割出双平面荧光透视 图像中导管的轮廓,并通过骨架化算法提取出导管的中心线。 接着研究了基于对极几何约束的立体视觉匹配方法,通过求解极 线与导管中心线的交点,求解出双平面投影中导管点集的对应关系,并结合投影模型与导管中心线构造空间射线,通过逐个求 解空间射线的相交点,将空间曲线重建问题转换成射线相交问题,实现导管三维空间形状的精确重建。 最后,为验证所提出介 入手术导管空间形状重建算法的可行性,进行了双平面透视图像重建导管实验,结果显示导管的最大形状重建误差<1. 55 mm, 均方误差<0. 89 mm,豪斯多夫距离不足 1. 49 mm。 表明所提出方法可实现介入手术导管三维形状的精确重建,为提升血管介 入手术精准导航和柔性导丝安全操控提供新方法和技术基础。

    Abstract:

    Interventional surgery is one of the primary methods for treating cardiovascular diseases. Current procedures mainly rely on 2D fluoroscopic images to guide surgeons, which cannot achieve three-dimensional visualization of interventional catheters during surgery, limiting surgical efficiency and safety. This paper addresses the clinical need for precise treatment in cardiovascular interventional surgery by proposing a method for reconstructing the spatial shape of interventional catheters based on the U-Net and epipolar geometry. First, the U-Net network is used to segment the catheter′s contours from biplane fluoroscopic images, and the catheter′s centerline is extracted using a skeletonization algorithm. Then, a stereo vision matching method based on epipolar geometry constraints is developed, where in the intersections of the epipolar lines and the catheter centerline are solved to determine the corresponding points in the biplane projections. By combining the projection model with the catheter centerline to construct spatial rays, the problem of spatial curve reconstruction is converted into a ray intersection problem, enabling accurate reconstruction of the catheter′s three-dimensional spatial shape. Finally, to verify the feasibility of the proposed catheter spatial shape reconstruction algorithm, experiments were conducted using biplane fluoroscopic images to reconstruct the catheter. The results showed that the maximum shape reconstruction error of the catheter was less than 1. 55 mm, the mean square error was less than 0. 89 mm, and the Hausdorff distance was less than 1. 49 mm. This indicates that the proposed method can achieve accurate reconstruction of the three-dimensional shape of interventional catheters, providing a new method and technical foundation for improving the precise navigation and safe manipulation of flexible guidewires in vascular interventional surgery

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王 康,何彦霖,黄宇辰,魏聚群,娄小平.基于 U-Net 网络和对极几何的介入导管空间形状重建方法[J].仪器仪表学报,2025,46(1):147-156

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  • 在线发布日期: 2025-04-08
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