TY - GEN
T1 - Delineating 3D angiogenic sprouting in OCT images via multiple active contours
AU - Xu, Ting
AU - Li, Fengqiang
AU - Nguyen, Duc Huy T.
AU - Chen, Christopher S.
AU - Zhou, Chao
AU - Huang, Xiaolei
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84890933230&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84890933230&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-40843-4_25
DO - 10.1007/978-3-642-40843-4_25
M3 - Conference contribution
AN - SCOPUS:84890933230
SN - 9783642408427
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 231
EP - 240
BT - Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions - 6th Int. Workshop, MIAR 2013 and 8th Int. Workshop, AE-CAI 2013, Held in Conjunction with MICCAI 2013, Proc.
T2 - 6th International Workshop on Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions, MIAR 2013 and 8th International Workshop, AE-CAI 2013, Held in Conjunction with MICCAI 2013
Y2 - 22 September 2013 through 22 September 2013
ER -