Abstract
In this paper, we propose a highly robust point-matching method (Graph Transformation Matching - GTM) relying on finding the consensus graph emerging from putative matches. Such method is a two-phased one in the sense that after finding the consensus graph it tries to complete it as much as possible. We successfully apply GTM to image registration in the context of finding mosaics from retinal images. Feature points are obtained after properly segmenting such images. In addition, we also introduce a novel topological descriptor for quantifying disease by characterizing the arterial/venular trees. Such descriptor relies on diffusion kernels on graphs. Our experiments have showed only statistical significance for the case of arterial trees, which is consistent with previous findings.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Aguilar, W.: Object recognition based on the structural correspondence of local features. Master’s thesis, UNAM, Mexico city (2006)
Chung, F.R.K.: Spectral graph theory. In: Conference Board of Mathematical Science CBMS, Providence, RI, American Matematical Society 92 (1997)
Chung, F.R.K., Yau, S.-T.: Coverings, heat kernels and spanning trees. Electronic Journal of Combinatorics 6 (1999)
Gelman, R., Martinez-Perez, M.E., Vanderveen, D.K., Moskowitz, A., Fulton, A.: Diagnosis of plus disease in retinopathy of prematurity using retinal image multisacle analysis (risa). Investigative Ophthalmology & Visual Science 46(12), 4734–4738 (2005)
Hughes, A.D., Martinez-Perez, M.E., Jabba, A.-S., Hassan, A., Witt, N.W., Mistry, P.D., Chapman, N., Stanton, A.V., Beevers, G., Pedrinelli, T., Parker, K.H., Thom, S.A.M.: Quantification of topological changes in retinal vascular architecture in essential and malignant hypertension. Journal of Hypertension 24(5), 889–894 (2006)
Kondor, R., Lafferty, J.: Diffusion kernels on graphs and other discrete input spaces. In: Proc. Intl. Conf. on Machine Learning, Los Alamitos, CA, pp. 315–322 (2002)
Lozano, M.A., Escolano, F.: A significant improvement of softassign with diffusion kernels. In: Fred, A., Caelli, T.M., Duin, R.P.W., Campilho, A., de Ridder, D. (eds.) Structural, Syntactic, and Statistical Pattern Recognition. LNCS, vol. 3138, pp. 76–84. Springer, Heidelberg (2004)
Martinez-Perez, M.E.: Computer Analysis of the Geometry of the Retinal Vasculature. PhD thesis, Imperial College, London, UK (2001)
Martinez-Perez, M.E., Hughes, A.D., Stanton, A.V., Thom, S.A., Chapman, N., Bharath, A.A., Parker, K.H.: Retinal vascular tree morphology: A semi-automatic quantification. IEEE Transactions on Biomedical Engineering 49(8), 912–917 (2002)
Martinez-Perez, M.E., Hughes, A.D., Thom, S.A., Bharath, A.A., Parker, K.H.: Segmentation of blood vessels from red-free and fluorescein retinal images. Medical Image Analysis 11(1), 47–61 (2007)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Aguilar, W., Martinez-Perez, M.E., Frauel, Y., Escolano, F., Lozano, M.A., Espinosa-Romero, A. (2007). Graph-Based Methods for Retinal Mosaicing and Vascular Characterization. In: Escolano, F., Vento, M. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2007. Lecture Notes in Computer Science, vol 4538. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72903-7_3
Download citation
DOI: https://doi.org/10.1007/978-3-540-72903-7_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72902-0
Online ISBN: 978-3-540-72903-7
eBook Packages: Computer ScienceComputer Science (R0)