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

机译:在OCT图像中描绘3D血管生成通过多个活跃轮廓

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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:最近光学相干断层扫描(OCT)的进展使得在体外使三维人工血管网络的高分辨率成像。图像分割可以帮助量化这些曲线网络的形态和拓扑特性,以促进对血管生成过程的定量研究。在这里,我们提出了一种描绘Scentral-Diame OCT成像的3D人工血管网络描绘的新方法。我们的方法采用多个拉伸开口有源轮廓(SOACS),该轮廓(SOACS)演变地演变以检索下面的血管网络的形态和拓扑。然后可以基于分段结果进行网络属性的量化。我们通过在模拟和真实OCT图像中分割3D人工脉管系统来展示所提出的方法的潜力。我们提供结位置和血管长度作为从OCT图像量化3D人工脉管系统的血管生成萌芽。

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