Abstract
In this paper, a multi-resolution rigid-model-based global matching algorithm is employed to register tree structures of blood vessels extracted from retinal fundus images. To further improve alignment of the vessels, a local structure-deformed elastic matching algorithm is proposed to eliminate the existence of ‘ghost vessels’ for accurate registration. The matching methods are tested on 268 pairs of retinal fundus images. Experiment results show that our global-to-local registration strategy is able to achieve an average centreline mapping errors of 1.85 pixels with average execution time of 207 seconds. The registration results have also been visually validated by corresponding fusion maps.
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You, X., Fang, B., He, Z., Tang, Y.Y. (2005). A Global-to-Local Matching Strategy for Registering Retinal Fundus Images. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3522. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492429_32
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DOI: https://doi.org/10.1007/11492429_32
Publisher Name: Springer, Berlin, Heidelberg
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