3D blood vessels segmentation from optical coherence tomography

Purpose To compute the 3D retinal vascular network, from standard high‐definition optical coherence tomography (HD‐OCT) data. Methods Abnormal retinal vascular patterns were shown to be related to retinal and cardiac diseases. Studies have been performed using 2D fundus images. However, the obtained...

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Bibliographic Details
Published in:Acta ophthalmologica (Oxford, England) England), 2012-09, Vol.90 (s249), p.0-0
Main Authors: GUIMARAES, P, RODRIGUES, P, BERNARDES, R, SERRANHO, P
Format: Article
Language:English
Subjects:
Blood
Ophthalmology
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Summary:Purpose To compute the 3D retinal vascular network, from standard high‐definition optical coherence tomography (HD‐OCT) data. Methods Abnormal retinal vascular patterns were shown to be related to retinal and cardiac diseases. Studies have been performed using 2D fundus images. However, the obtained measurements may suffer from missing depth information for improved quantitative accuracy. In this work we resorted to Cirrus HD‐OCT data (Carl Zeiss Meditec, Inc., Dublin, CA, USA) to scan the human macula. Our approach to obtain vessel positioning (depth‐wise) takes advantage of the 2D automatic vessel segmentation of an OCT fundus image. To locate vessels in depth, we compare A‐scans where in the fundus image no vessels were detected to neighbor A‐scans containing vessels. Hence, we are able to identify the location of particular landmarks that characterize the presence of a vessel, such as, the hyper‐reflectivity and the shadowing effect (due to the light absorption by blood). Results Our algorithm is able to locate both above‐mentioned vessel markers (hyper‐reflective region and shadow). Preliminary data shows promising results. Both markers present good robustness and coherence, as demonstrated by the smoothness of vessels across different B‐scans and the possibility to discriminate between different depth paths of crossing vessels. Conclusion The findings suggest the possibility to compute the 3D vascular network, noninvasively, using a standard high‐definition OCT. Additionally, accounting for vessel depth will lead to improved measurements of retinal vascular network properties and therefore to possible better correlations between its shape, location, and disease status.
ISSN:1755-375X
1755-3768
DOI:10.1111/j.1755-3768.2012.2712.x