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Proceedings Paper

Automated feature extraction for retinal vascular biometry in zebrafish using OCT angiography
Author(s): Ivan Bozic; Gopikrishna M. Rao; Vineet Desai; Yuankai K. Tao
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Paper Abstract

Zebrafish have been identified as an ideal model for angiogenesis because of anatomical and functional similarities with other vertebrates. The scale and complexity of zebrafish assays are limited by the need to manually treat and serially screen animals, and recent technological advances have focused on automation and improving throughput. Here, we use optical coherence tomography (OCT) and OCT angiography (OCT-A) to perform noninvasive, in vivo imaging of retinal vasculature in zebrafish. OCT-A summed voxel projections were low pass filtered and skeletonized to create an en face vascular map prior to connectivity analysis. Vascular segmentation was referenced to the optic nerve head (ONH), which was identified by automatically segmenting the retinal pigment epithelium boundary on the OCT structural volume. The first vessel branch generation was identified as skeleton segments with branch points closest to the ONH, and subsequent generations were found iteratively by expanding the search space outwards from the ONH. Biometric parameters, including length, curvature, and branch angle of each vessel segment were calculated and grouped by branch generation. Despite manual handling and alignment of each animal over multiple time points, we observe distinct qualitative patterns that enable unique identification of each eye from individual animals. We believe this OCT-based retinal biometry method can be applied for automated animal identification and handling in high-throughput organism-level pharmacological assays and genetic screens. In addition, these extracted features may enable high-resolution quantification of longitudinal vascular changes as a method for studying zebrafish models of retinal neovascularization and vascular remodeling.

Paper Details

Date Published: 8 February 2017
PDF: 4 pages
Proc. SPIE 10045, Ophthalmic Technologies XXVII, 100450J (8 February 2017); doi: 10.1117/12.2252370
Show Author Affiliations
Ivan Bozic, Vanderbilt Univ. (United States)
Gopikrishna M. Rao, Vanderbilt Univ. (United States)
Vineet Desai, Vanderbilt Univ. (United States)
Yuankai K. Tao, Vanderbilt Univ. (United States)

Published in SPIE Proceedings Vol. 10045:
Ophthalmic Technologies XXVII
Fabrice Manns; Per G. Söderberg; Arthur Ho, Editor(s)

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