“Estrategia para la detección de tipos de enfermedades oculares usando red neuronal SOM“
Ver/
Descargar
(application/pdf: 971.2Kb)
(application/pdf: 971.2Kb)
Fecha
2022-07-18Autor(es)
Huarote Zegarra, Raúl Eduardo
Vega Luján, Yensi
Flores Masías, Edward José
lCuba Aguilar, Cesar Rau
Llanos Chacaltana, Katherine Susan
Larios Franco, Alfredo Cesar
Diaz Reategui, Monica
Metadatos
Mostrar el registro completo del ítemResumen
“This research aims to cover a need to be able to
classify according to the funds of eyes in diabetic retinopathy
disease, how to convert to gray tone, perform an equalization,
apply the canny edge highlighting algorithm and apply
morphological operations so that a SOM (self-organization ma p )
neural network can be entered and classified. To achieve this, it is
classified as 0 to diabetic retinopathy, 1 to glaucoma and 3 to
healthy eyes. To corroborate this strategy, a public database of
Fundus-images has been taken, being 45 images of eyes for
training and for tests 15 images that were not part of the training
were used and for the tests 3 images that were not part of the
training were used and each grayscale image is scaled to a
dimension of 256x256 pixels, managing to demonstrate with this
strategy an affectivity of 93.7% certainty in the identification of
class of eye disease“
Colecciones
- SCOPUS [380]