Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/69793
Título: Adaptive threshold based automated identification of severity of diabetic macular edema from retinal images
Autores/as: Gupta, Varun
Sengar, Namita
Dutta, Malay Kishore
Travieso González, Carlos Manuel 
Clasificación UNESCO: 3314 Tecnología médica
Palabras clave: Diabetic Macular Edema
Exudates
Macula
Morphological
Optic Disc, et al.
Fecha de publicación: 2018
Publicación seriada: Frontiers in Artificial Intelligence and Applications 
Conferencia: 1st International Conference on Applications of Intelligent Systems, APPIS 2018 
Resumen: In this paper an algorithm is proposed for detection of severity of Diabetic Macular Edema (DME) from Retinal Images, which are invariant to image rotation. The proposed work includes detection of optic disc, macula, exudates, region of interest localization and a level indicator which indicates the severity of disease as severe, moderate or normal DME. Rotation Invariant detection of macula makes this method efficient. A set of NPDR data of fundus image of an eye is used to test the proposed algorithm. The results show a better comprehensive performance of disease severity checker and computationally efficient.
URI: http://hdl.handle.net/10553/69793
ISBN: 9781614999287
ISSN: 0922-6389
Fuente: Frontiers in Artificial Intelligence and Applications [ISSN 0922-6389], v. 310, p. 336-344
Colección:Actas de congresos
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