Classification of diabetic retinopathy using neural networks

被引：0

作者：

Nguyen, HT ^{[1
]}

Butler, M ^{[1
]}

Roychoudhry, A ^{[1
]}

Shannon, AG ^{[1
]}

Flack, J ^{[1
]}

Mitchell, P ^{[1
]}

机构：

[1] Univ Technol Sydney, Sydney, NSW 2007, Australia

来源：

PROCEEDINGS OF THE 18TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOL 18, PTS 1-5 | 1997年 / 18卷

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D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Classification of the severity of diabetic retinopathy (DR) and quantification of diabetic changes are viral for assessing the therapies and risk factors for this frequent complication of diabetes. A multilayer feedforward network has been developed for the classification of DR. One of its major strengths is that accurate feature extractions and accurate grading of DR lesions are not required. Another strength of this technique is its robustness as the network can also classify DR effectively in noisy environments.

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页码：1548 / 1549

页数：2

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