Multiple ocular diseases detection by graph regularized multi-label learning
Abstract
We develop a general framework for multiple ocular diseases diagnosis, based on Graph Regularized Multi-label Learning (GRML). Glaucoma, Pathological Myopia (PM), and Age-related Macular Degeneration (AMD) are three leading ocular diseases in the world. By exploiting the correlations among these three diseases, a novel GRML scheme is investigated for a simultaneous detection of these three leading ocular diseases for a given fundus image. We validate our GRML framework by conducting extensive experiments on SiMES dataset. The results show area under curve (AUC) of the receiver operating characteristic curve in multiple ocular diseases detection are much better than traditional popular algorithms. The method could be used for glaucoma, PM, and AMD diagnosis.
How to Cite:
Chen, X., Xu, Y., Duan, L., Zhang, Z., Wong, D. W. & Liu, J., (2014) “Multiple ocular diseases detection by graph regularized multi-label learning”, Proceedings of the Ophthalmic Medical Image Analysis International Workshop Archive 1(2014), 17-24. doi: https://doi.org/10.17077/omia.1004
Rights: Copyright © 2014, Xiangyu Chen, Yanwu Xu, Lixin Duan, Zhuo Zhang, Damon Wing Kee Wong, and Jiang Liu.
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