Automatic Detection of Glaucoma Using Disc Optic Segmentation and Feature Extraction
Maila Claro$^{1}$, L. Santos$^{1}$, Wallinson Silva$^{1}$, Flávio Henrique$^{1}$, Alcilene Sousa$^{2}$, Andre Macedo Santana$^{1}$
$^{1}$Univeridade Federal do Piauí. Brazil,
$^{2}$Universidade Federal do Maranhão. Brazil
email: claromaila@gmail.com, leonardo.moura.software@gmail.com, iwallinsom@gmail.com, flavio86@ufpi.edu.br, alcileneluzsousa@gmail.com, andremacedo@ufpi.edu.br

Schedule:Wed 21st@16:15, Room: D

Digital image processing is highlighted in the medical setting for automatic diagnosis of diseases. Glaucoma has no cure, and is the second leading cause of blindness wordwide. Currently there are treatments to prevent vision loss, but the disease must be discovered still in the early stages. Thus, this study aims to develop an automatic detection method of Glaucoma in retinal images. The methodology used in the study was: image acquisition, segmentation of the optic disc area (DO) in retinal images, color feature extraction and entropy in the targeted area and shortly after the selection of attributes. Finally, classification of images was conducted to determine wether or not glaucoma was present.

BibTex

@InProceedings{CLEI-2015:144377,
	author 		= {Maila Claro and L. Santos and Wallinson Silva and Flávio Henrique and Alcilene Sousa and Andre Macedo Santana},
	title 		= {Automatic Detection of Glaucoma Using Disc Optic Segmentation and Feature Extraction},
	booktitle 	= {2015 XLI Latin American Computing Conference (CLEI)},
	pages 		= {--23},
	year 		= {2015},
	editor 		= {Hector Cancela and Alex Cuadros-Vargas and Ernesto Cuadros-Vargas},
	address 	= {Arequipa-Peru},
	month 		= {October},
	organization 	= {CLEI},
	publisher 	= {CLEI},
	url 		= {http://clei.org/clei2015/144377},
	isbn 		= {978-1-4673-9143-6},
	}