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. © 2013 Springer-Verlag.
CITATION STYLE
Xu, T., Li, F., Nguyen, D. H. T., Chen, C. S., Zhou, C., & Huang, X. (2013). Delineating 3D angiogenic sprouting in OCT images via multiple active contours. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8090 LNCS, pp. 231–240). https://doi.org/10.1007/978-3-642-40843-4_25
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