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3D surface reconstruction of retinal vascular structures

机译:视网膜血管结构的3D表面重建

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摘要

We propose in this paper, a three-dimensional surface reconstruction of a retinal vascular network from a pair of 2D retinal images. Our approach attempts to address the above challenges by incorporating an epipolar geometry estimation and adaptive surface modelling in a 3D reconstruction, using three steps: segmentation, 3D skeleton reconstruction and 3D surface modelling of vascular structures. The intrinsic calibration matrices are found via the solution of simplified Kruppa equations. A simple essential matrix based on a self-calibration method has been used for the 'fundus camera-eye' system. The used method has eventually produced vessel surfaces that could be fit for various applications, such as applications for computational fluid dynamics simulations and applications for real-time virtual interventional.
机译:我们在本文中提出了从一对2D视网膜图像对视网膜血管网络进行三维表面重建的方法。我们的方法试图通过将对极几何估计和自适应表面建模合并到3D重建中来解决上述挑战,该过程使用以下三个步骤:分割,3D骨骼重建和血管结构的3D表面建模。通过简化的Kruppa方程的解可以找到内在的校准矩阵。一个基于自校准方法的简单基本矩阵已用于“眼底摄像眼”系统。所使用的方法最终产生了可以适合各种应用的血管表面,例如用于计算流体动力学模拟的应用和用于实时虚拟介入的应用。

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