A new intelligent system for glaucoma disease detection
| Autor: | Amel Feroui, Mohammed El Amine Lazouni, Saïd Mahmoudi |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Majority rule
genetic structures business.industry Computer science Decision tree k-means clustering General Engineering Glaucoma 020206 networking & telecommunications Pattern recognition 02 engineering and technology Mathematical morphology Perceptron medicine.disease Computer Science Applications Support vector machine ComputingMethodologies_PATTERNRECOGNITION 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing Segmentation Artificial intelligence business Software |
| Zdroj: | International Journal of Computer Aided Engineering and Technology. 11:613 |
| ISSN: | 1757-2665 1757-2657 |
| DOI: | 10.1504/ijcaet.2019.100457 |
| Popis: | Glaucoma is a redundant disease and a major cause of blindness resulting from damage in the optic nerve. This disease generally spreads very slowly and does not show any symptom at the beginning. The research presented in this paper is both a clinical and a technological aid for diagnosis of early glaucoma based on four different artificial intelligence classification techniques, which are: multi-layer perceptron, support vector machine, K-nearest neighbour and decision tree. A majority vote system was applied to these techniques in order to optimize the performances of the proposed system. As far as the ratio cup to disc, which is one of the descriptors of the collected database, in this paper we detect automatically the cup by the k-means algorithm and the disc using mathematical morphology method. Moreover, we proposed a contour adjustment technique (Ellipse Fitting). The obtained results are satisfying, promising, and prove the efficiency and the coherence of our new database. |
| Databáze: | OpenAIRE |
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