Parabolic model is commonly used for fovea and macular detection. But, the center of an optic disc is mostly taken as the vertex of the parabola-like vasculature. Since vessels generate out from the vessel origin, taking vessel origin as the vertex can provide better fovea localization than taking optic disc center. Recently, the vessel origin is also used to detect vessels within an optic disc. However, there is no published research for finding the exact vessel origin position. This paper proposed a novel method to locate the position of vessel origin. First, a retinal image is processed to get the vascular structure. Then, four features based on the characteristic of vessel origin are selected, and Bayesian classifier is applied to locate the vessel origin. The proposed method is evaluated on the publicly available database, DRIVE. The experimental results show that the average Euclidean distance between the vessel origin and the one marked by experts are 13.3 pts, which are much better than other methods. This can further provide a more accurate vessel and fovea detection. © 2013 Springer-Verlag.
CITATION STYLE
Yu, C. Y., Liu, C. C., Wu, J. L., Yu, S. S., & Huang, J. Y. (2013). A study of vessel origin detection on retinal images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7906 LNAI, pp. 620–625). https://doi.org/10.1007/978-3-642-38577-3_64
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