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- W4245394497 abstract "In this work we compare two methods for automatic optic nerve (ON) localization in retinal imagery. The first method uses a Bayesian decision theory discriminator based on four spatial features of the retina imagery. The second method uses a principal component-based reconstruction to model the ON. We report on an improvement to the model-based technique by incorporating linear discriminant analysis and Bayesian decision theory methods. We explore a method to combine both techniques to produce a composite technique with high accuracy and rapid throughput. Results are shown for a data set of 395 images with 2-fold validation testing" @default.
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- W4245394497 date "2006-08-01" @default.
- W4245394497 modified "2023-09-25" @default.
- W4245394497 title "Locating the Optic Nerve in Retinal Images: Comparing Model-Based and Bayesian Decision Methods" @default.
- W4245394497 doi "https://doi.org/10.1109/iembs.2006.4398436" @default.
- W4245394497 hasPublicationYear "2006" @default.
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