Abstract
The retinal vascular network is directly observable by non-invasive techniques, and changes of its status have been associated to retinal and cardiac pathologies. In order to infer on these changes, studies have been performed using 2D fundus images. However, measurements such as vessel tortuosity or bifurcation angle suffer from missing depth information.
In this work we aim to consider the retinal vascular network in 3D as imaged by optical coherence tomography (OCT). We take advantage of proprietary software developed by our research group able to segment the vascular network from OCT fundus reference images (personal communication). This approach allows for the comparison between vessel and non-vessel A-scans and thus to highlight differences such as the hyper-reflectivity and the shadows casted by vessels.
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References
Witt, N., Wong, T.Y., Hughes, A.D., Chaturvedi, N., Klein, B.E., Evans, R., McNamara, M., Thom, S.A., Klein, R.: Abnormalities of retinal microvascular structure and risk of mortality from ischemic heart disease and stroke. Hypertension 47, 975–981 (2006)
Kwa, V.I., van der Sande, J.J., Stam, J., Tijmes, N., Vrooland, J.L.: Retinal arterial changes correlate with cerebral small-vessel disease. Neurology 59, 1536–1540 (2002)
Drexler, W., Fujimoto, J.G.: Optical Coherence Tomography: Technology and Applications. Springer (2008)
Niemeijer, M., Garvin, M., van Ginnekan, B., Sonka, M., Abràmoff, M.: Vessel Segmentation in 3D Spectral OCT Scans of the Retina. In: Proc. SPIE, vol. 6914, p. 69141R-1-8 (2008), doi:10.1117/12.772680
Salem, N., Salem, S., Nandi, A.: Segmentation of retinal blood vessels based on analysis of the Hessian Matrix and Clustering Algorithm. In: 15th European Signal Processing Conference, pp. 428–432 (2007)
Lee, T.: Image Representation Using 2D Gabor Wavelets. IEEE Trans. Pattern Anal. Mach. Intell. 18(10), 959–971 (1996)
Kovesi, P.: Image Features from Phase Congruency. Videre: A Journal of Computer Vision Research 1(3) (1999)
Kovesi, P.: Symmetry and Asymmetry from Local Phase. In: Proc. Tenth Australian Joint Conference on Artificial Intelligence, pp. 185–190 (1997)
Orfanidis, S.J.: Introduction to Signal Processing. Prentice-Hall, Englewood Cliffs (1996)
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Guimarães, P., Rodrigues, P., Serranho, P., Bernardes, R. (2012). 3D Retinal Vascular Network from Optical Coherence Tomography Data. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2012. Lecture Notes in Computer Science, vol 7325. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31298-4_40
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DOI: https://doi.org/10.1007/978-3-642-31298-4_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31297-7
Online ISBN: 978-3-642-31298-4
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