Abstract
This paper presents an automatic approach for artery/vein (A/V) classification based on the analysis of a graph representing the structure of the retinal vasculature. The entire vascular tree is classified by deciding on the type of each intersection point (graph node) and assigning one of two classes to each vessel segment (graph link). The final label for each vessel segment is accomplished by a combination of structural information taken from the graph (link class) with intensity features measured in the original color image. An accuracy of 88.0% was achieved for the 40 images of the INSPIRE-AVR dataset, thus demonstrating that our method outperforms state-of-the-art approaches for A/V classification.
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References
Nguyen, T.T., Wong, T.Y.: Retinal vascular changes and diabetic retinopathy. Current Diabetes Reports 9, 277–283 (2009)
Guan, K., Hudson, C., Wong, T., Kisilevsky, M., Nrusimhadevara, R.K., Lam, W.C., Mandelcorn, M., Devenyi, R.G., Flanagan, J.G.: Retinal hemodynamics in early diabetic macular edema. Diabetes 55, 813–818 (2006)
Neubauer, A.S., Ludtke, M., Haritoglou, C., Priglinger, S., Kampik, A.: Retinal vessel analysis reproducibility in assessing cardiovascular disease. Optometry and Vision Science 85, 247–254 (2008)
Lesage, S.R., Mosley, T.H., Wong, T.Y., Szklo, M., Knopman, D., Catellier, D.J., Cole, S.R., Klein, R., Coresh, J., Coker, L.H., Sharrett, A.R.: Retinal microvascular abnormalities and cognitive decline: the aric 14-year follow-up study. Neurology 73, 862–868 (2009)
Knudtson, M.D., Lee, K.E., Hubbard, L.D., Wong, T.Y., Klein, R., Klein, B.E.K.: Revised formulas for summarizing retinal vessel diameters. Current Eye Research 27, 143–149 (2003)
Rothaus, K., Jiang, X., Rhiem, P.: Separation of the retinal vascular graph in arteries and veins based upon structural knowledge. Image Vision Comput. 27, 864–875 (2009)
Vazquez, S., Cancela, B., Barreira, N., Penedo, M., Saez, M.: On the automatic computation of the arterio-venous ratio in retinal images: Using minimal paths for the artery/vein classification. In: International Conference on Digital Image Computing: Techniques and Applications (DICTA), pp. 599–604 (2010)
Kondermann, C., Kondermann, D., Yan, M.: Blood vessel classification into arteries and veins in retinal images. In: SPIE, pp. 651247–651249 (2007)
Niemeijer, M., Xu, X., Dumitrescu, A., Gupta, P., van Ginneken, B., Folk, J., Abràmoff, M.: Automated measurement of the arteriolar-to-venular width ratio in digital color fundus photographs. IEEE Trans. Medical Imaging 30, 1941–1950 (2011)
Mendonça, A., Campilho, A.: Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction. IEEE Transactions on Medical Imaging 25, 1200–1213 (2006)
Mendonça, A., Dashtbozorg, B., Campilho, A.: Segmentation of the vascular network of the retina. In: Ng, E.Y.K., Acharya, U.R., Suri, J.S., Campilho, A. (eds.) Image Analysis and Modeling in Opthalmology. CRC Press (to be published, 2013)
Niemeijer, M., Xu, X., Dumitrescu, A., Gupta, P., van Ginneken, B., Folk, J., Abràmoff, M.: INSPIRE-AVR:Iowa Normative Set for Processing Images of the REtina-Artery Vein Ratio, http://webeye.ophth.uiowa.edu/component/k2/item/270
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Dashtbozorg, B., Mendonça, A.M., Campilho, A. (2013). Automatic Classification of Retinal Vessels Using Structural and Intensity Information. In: Sanches, J.M., Micó, L., Cardoso, J.S. (eds) Pattern Recognition and Image Analysis. IbPRIA 2013. Lecture Notes in Computer Science, vol 7887. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38628-2_71
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DOI: https://doi.org/10.1007/978-3-642-38628-2_71
Publisher Name: Springer, Berlin, Heidelberg
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