AUTOMATIC METHOD FOR GLAUCOMA CLASSIFICATION USING TEXTURE ANALYSIS, XGBOOST AND GRID SEARCH

Nonato Rodrigues de Sales Carvalho, Antônio Oseas de Carvalho Filho, Thiago José Barbosa Lima, Francisco das Chagas A. C. Júnior, Maria da Conceição Leal Carvalho Rodrigues, Pablo Vieira de Abreu, Rafael Luz Araújo, Deusimar Damião de Sousa

Resumo


Glaucoma is an irreversible pathology, generated by increased intraocular pressure. Early detection is critical and can pre- vent total vision loss. Clinical examinations are commonly used to detect the disease. Still, the time and cost of identi- fication is quite high. This paper presents a computational methodology that aims to assist specialists in the discov- ery of glaucoma through Computer Vision techniques. The proposed methodology consists in the application of several texture descriptors combined with a parameter optimiza- tion done through Grid search with the XGBoost classifier. A result was obtained with accuracy of 82.37% and ROC of 82.08%.


Palavras-chave


Glaucoma; Grid search; XGBoost.

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Revista de Sistemas e Computação. ISSN 2237-2903