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Delineating 3D Angiogenic Sprouting in OCT Images via Multiple Active Contours

机译:通过多个活动轮廓描绘OCT图像中的3D血管发芽

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Recent advances in Optical Coherence Tomography (OCT) has enabled high resolution imaging of three dimensional artificial vascular networks in vitro. Image segmentation can help quantify the morphological and topological properties of these curvilinear networks to facilitate quantitative study of the angiogenic process. Here we present a novel method to delineate the 3D artificial vascular networks imaged by spectral-domain OCT. Our method employs multiple Stretching Open Active Contours (SOACs) that evolve synergistically to retrieve both the morphology and topology of the underlying vascular networks. Quantification of the network properties can then be conducted based on the segmentation result. We demonstrate the potential of the proposed method by segmenting 3D artificial vasculature in simulated and real OCT images. We provide junction locations and vessel lengths as examples for quantifying angiogenic sprouting of 3D artificial vasculature from OCT images.
机译:光学相干断层扫描(OCT)的最新进展已使高分辨率的三维人工血管网络能够在体外成像。图像分割可以帮助量化这些曲线网络的形态和拓扑特性,以促进血管生成过程的定量研究。在这里,我们提出了一种新颖的方法来描绘由光谱域OCT成像的3D人工血管网络。我们的方法采用协同扩展的多个拉伸开放主动轮廓(SOAC),以检索基础血管网络的形态和拓扑。然后,可以基于分割结果对网络属性进行量化。我们通过在模拟和实际OCT图像中分割3D人工脉管系统来证明所提出方法的潜力。我们提供了接合点位置和血管长度,以作为定量从OCT图像中量化3D人工血管的新生血管的实例。

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