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Journal
2004 | 2 | 1 | 12-24
Article title

Statistical and neural net methods for automatic glaucoma diagnosis determination

Content
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Languages of publication
EN
Abstracts
EN
Two new computer diagnostic methods for the automatic determination of glaucoma diagnosis are presented and compared in this paper: the statistical method and the neural net method. Both introduced methods evaluate colour glaucomatous changes within the optic disc area. The mentioned colour changes are numerically represented using a suitable image analysis process. Next, the investigated eye is classified to three defined glaucoma-risk classes with different reliability of the diagnosis determination. The verification and the reliability comparison of both studied methods are performed by virtue of the application of this methods to a set of normal healthy optic disc images and a set of glaucomatous optic disc images.
Publisher

Journal
Year
Volume
2
Issue
1
Pages
12-24
Physical description
Dates
published
1 - 3 - 2004
online
1 - 3 - 2004
Contributors
  • Department of Experimental Physics and Joint Laboratory of Optics of Palacký, University and Institute of Physics of Academy of Sciences, 17 listopadu 50a, 772 07, Olomouc, Czech Republic, pluhacek@prfnw.upol.cz
  • Department of Experimental Physics and Joint Laboratory of Optics of Palacký, University and Institute of Physics of Academy of Sciences, 17 listopadu 50a, 772 07, Olomouc, Czech Republic, jpospis@risc.upol.cz
References
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  • [12] F. Pluháček, J. Pospíšil: “Present methods of the computer-image analysis of a human retina with regard to diagnostics of glaucoma”, Fine Mechanics and Optics, Vol. 46, (2001), pp. 326–334.
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Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.-psjd-doi-10_2478_BF02476270
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