21 July 2017 Automated detection of age-related macular degeneration in OCT images using multiple instance learning
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Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 104203V (2017) https://doi.org/10.1117/12.2282522
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China
Abstract
Age-related Macular Degeneration (AMD) is a kind of macular disease which mostly occurs in old people,and it may cause decreased vision or even lead to permanent blindness. Drusen is an important clinical indicator for AMD which can help doctor diagnose disease and decide the strategy of treatment. Optical Coherence Tomography (OCT) is widely used in the diagnosis of ophthalmic diseases, include AMD. In this paper, we propose a classification method based on Multiple Instance Learning (MIL) to detect AMD. Drusen can exist in a few slices of OCT images, and MIL is utilized in our method. We divided the method into two phases: training phase and testing phase. We train the initial features and clustered to create a codebook, and employ the trained classifier in the test set. Experiment results show that our method achieved high accuracy and effectiveness.
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Weiwei Sun, Xiaoming Liu, Zhou Yang, "Automated detection of age-related macular degeneration in OCT images using multiple instance learning", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104203V (21 July 2017); doi: 10.1117/12.2282522; https://doi.org/10.1117/12.2282522
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