Analysing visual field and diagnosing glaucoma progression using a hybrid of per location differences and artificial neural network ensembles
Visual function test results for glaucoma diagnosis is perceived to be subjective and problematic.In this paper, we aim to address the issues and problems associated with these current approaches.We present (a) a system architecture for analyzing visual field and diagnosing glaucoma progression; (b)...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2004
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| Subjects: | |
| Online Access: | http://repo.uum.edu.my/13849/1/KM119.pdf http://repo.uum.edu.my/13849/ http://www.kmice.cms.net.my |
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| Summary: | Visual function test results for glaucoma diagnosis is perceived to be subjective and problematic.In this paper, we aim to address the issues and problems associated with these current approaches.We present (a) a system architecture for analyzing visual field and diagnosing glaucoma progression; (b) a per location differences approach for analyzing visual field to obtain measurements of glaucoma progression;
and (c) a neural network ensemble approach where several artifial neural network are jointly used to diagnose glaucoma progression.It is hoped that it would be possible to diagnose glaucoma progression with just one reading of a patient’s visual field. |
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