Please use this identifier to cite or link to this item: https://doi.org/10.1109/IEMBS.2011.6090724
Title: Model-based optic nerve head segmentation on retinal fundus images
Authors: Yin, F.
Liu, J.
Ong, S.H. 
Sun, Y. 
Wong, D.W.K.
Tan, N.M.
Cheung, C.
Baskaran, M.
Aung, T.
Wong, T.Y. 
Issue Date: 2011
Source: Yin, F.,Liu, J.,Ong, S.H.,Sun, Y.,Wong, D.W.K.,Tan, N.M.,Cheung, C.,Baskaran, M.,Aung, T.,Wong, T.Y. (2011). Model-based optic nerve head segmentation on retinal fundus images. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS : 2626-2629. ScholarBank@NUS Repository. https://doi.org/10.1109/IEMBS.2011.6090724
Abstract: The optic nerve head (optic disc) plays an important role in the diagnosis of retinal diseases. Automatic localization and segmentation of the optic disc is critical towards a good computer-aided diagnosis (CAD) system. In this paper, we propose a method that combines edge detection, the Circular Hough Transform and a statistical deformable model to detect the optic disc from retinal fundus images. The algorithm was evaluated against a data set of 325 digital color fundus images, which includes both normal images and images with various pathologies. The result shows that the average error in area overlap is 11.3% and the average absolute area error is 10.8%, which outperforms existing methods. The result indicates a high correlation with ground truth segmentation and thus demonstrates a good potential for this system to be integrated with other retinal CAD systems. © 2011 IEEE.
Source Title: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
URI: http://scholarbank.nus.edu.sg/handle/10635/70972
ISBN: 9781424441211
ISSN: 1557170X
DOI: 10.1109/IEMBS.2011.6090724
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