Estrategia para la detección de tipos de enfermedades oculares usando red neuronal SOM

Huarote Zegarra Raúl Eduardo; Vega Luján Yensi; Flores Masías Edward José; Cesar Raul Cuba Aguilar; Katherine Susan Llanos Chacaltana; Larios Franco Alfredo Cesar; Diaz Reategui Monica

doi:10.18687/LACCEI2022.1.1.578

Estrategia para la detección de tipos de enfermedades oculares usando red neuronal SOM

Huarote Zegarra Raúl Eduardo
, Vega Luján Yensi
, Flores Masías Edward José
, Cesar Raul Cuba Aguilar
, Katherine Susan Llanos Chacaltana
, Larios Franco Alfredo Cesar
, Diaz Reategui Monica

Facultad de Ingeniería de la UPN

Universidad Nacional Tecnológica De Lima Sur
Universidad Nacional de Trujillo
Universidad Nacional Federico Villarreal
Universidad Norbert Wiener

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

1 Cita (Scopus)

Resumen

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 map) 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.

Título traducido de la contribución	Strategy for the detection of types of eye diseases using SOM neural network
Idioma original	Español
Título de la publicación alojada	20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology
Subtítulo de la publicación alojada	"Education, Research and Leadership in Post-Pandemic Engineering: Resilient Inclusive and Sustainable Actions", LACCEI 2022
Editores	Maria M. Larrondo Petrie, Jose Texier, Andrea Pena, Jose Angel Sanchez Viloria
ISBN (versión digital)	9786289520705
DOI	https://doi.org/10.18687/LACCEI2022.1.1.578
Estado	Publicada - 2022
Evento	20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, LACCEI 2022 - Boca Raton, Estados Unidos Duración: 18 jul. 2022 → 22 jul. 2022

Serie de la publicación

Nombre	Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volumen	2022-July
ISSN (versión digital)	2414-6390

Conferencia

Conferencia	20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, LACCEI 2022
País/Territorio	Estados Unidos
Ciudad	Boca Raton
Período	18/07/22 → 22/07/22

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 3: Salud y bienestar

Palabras clave

diabetic retinopathy
diabeticretinopathy
eyes
eyes
glaucoma
glaucoma
SOM neural network
SOM neural network
Strategy
Strategy

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10.18687/LACCEI2022.1.1.578

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Eduardo, H. Z. R., Yensi, V. L., José, F. M. E., Aguilar, C. R. C., Chacaltana, K. S. L., Cesar, L. F. A., & Monica, D. R. (2022). Estrategia para la detección de tipos de enfermedades oculares usando red neuronal SOM. En M. M. Larrondo Petrie, J. Texier, A. Pena, & J. A. S. Viloria (Eds.), 20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: "Education, Research and Leadership in Post-Pandemic Engineering: Resilient Inclusive and Sustainable Actions", LACCEI 2022 (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2022-July). https://doi.org/10.18687/LACCEI2022.1.1.578

Eduardo, Huarote Zegarra Raúl ; Yensi, Vega Luján ; José, Flores Masías Edward et al. / Estrategia para la detección de tipos de enfermedades oculares usando red neuronal SOM. 20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: "Education, Research and Leadership in Post-Pandemic Engineering: Resilient Inclusive and Sustainable Actions", LACCEI 2022. editor / Maria M. Larrondo Petrie ; Jose Texier ; Andrea Pena ; Jose Angel Sanchez Viloria. 2022. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology).

@inproceedings{eda4311f466843bda65f00ce4df86e65,

title = "Estrategia para la detecci{\'o}n de tipos de enfermedades oculares usando red neuronal SOM",

abstract = "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 map) 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.",

keywords = "diabetic retinopathy, diabeticretinopathy, eyes, eyes, glaucoma, glaucoma, SOM neural network, SOM neural network, Strategy, Strategy",

author = "Eduardo, \{Huarote Zegarra Ra{\'u}l\} and Yensi, \{Vega Luj{\'a}n\} and Jos{\'e}, \{Flores Mas{\'i}as Edward\} and Aguilar, \{Cesar Raul Cuba\} and Chacaltana, \{Katherine Susan Llanos\} and Cesar, \{Larios Franco Alfredo\} and Monica, \{Diaz Reategui\}",

note = "Publisher Copyright: {\textcopyright} 2022 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.; 20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, LACCEI 2022 ; Conference date: 18-07-2022 Through 22-07-2022",

year = "2022",

doi = "10.18687/LACCEI2022.1.1.578",

language = "Espa{\~n}ol",

series = "Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology",

editor = "\{Larrondo Petrie\}, \{Maria M.\} and Jose Texier and Andrea Pena and Viloria, \{Jose Angel Sanchez\}",

booktitle = "20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology",

}

Eduardo, HZR, Yensi, VL, José, FME, Aguilar, CRC, Chacaltana, KSL, Cesar, LFA & Monica, DR 2022, Estrategia para la detección de tipos de enfermedades oculares usando red neuronal SOM. En MM Larrondo Petrie, J Texier, A Pena & JAS Viloria (eds.), 20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: "Education, Research and Leadership in Post-Pandemic Engineering: Resilient Inclusive and Sustainable Actions", LACCEI 2022. Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology, vol. 2022-July, 20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, LACCEI 2022, Boca Raton, Estados Unidos, 18/07/22. https://doi.org/10.18687/LACCEI2022.1.1.578

Estrategia para la detección de tipos de enfermedades oculares usando red neuronal SOM. / Eduardo, Huarote Zegarra Raúl; Yensi, Vega Luján; José, Flores Masías Edward et al.
20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: "Education, Research and Leadership in Post-Pandemic Engineering: Resilient Inclusive and Sustainable Actions", LACCEI 2022. ed. / Maria M. Larrondo Petrie; Jose Texier; Andrea Pena; Jose Angel Sanchez Viloria. 2022. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2022-July).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - Estrategia para la detección de tipos de enfermedades oculares usando red neuronal SOM

AU - Eduardo, Huarote Zegarra Raúl

AU - Yensi, Vega Luján

AU - José, Flores Masías Edward

AU - Aguilar, Cesar Raul Cuba

AU - Chacaltana, Katherine Susan Llanos

AU - Cesar, Larios Franco Alfredo

AU - Monica, Diaz Reategui

PY - 2022

Y1 - 2022

N2 - 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 map) 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.

AB - 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 map) 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.

KW - diabetic retinopathy

KW - diabeticretinopathy

KW - eyes

KW - glaucoma

KW - SOM neural network

KW - Strategy

UR - https://www.scopus.com/pages/publications/85140001562

U2 - 10.18687/LACCEI2022.1.1.578

DO - 10.18687/LACCEI2022.1.1.578

M3 - Contribución a la conferencia

AN - SCOPUS:85140001562

T3 - Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology

BT - 20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology

A2 - Larrondo Petrie, Maria M.

A2 - Texier, Jose

A2 - Pena, Andrea

A2 - Viloria, Jose Angel Sanchez

T2 - 20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, LACCEI 2022

Y2 - 18 July 2022 through 22 July 2022

ER -

Eduardo HZR, Yensi VL, José FME, Aguilar CRC, Chacaltana KSL, Cesar LFA et al. Estrategia para la detección de tipos de enfermedades oculares usando red neuronal SOM. En Larrondo Petrie MM, Texier J, Pena A, Viloria JAS, editores, 20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: "Education, Research and Leadership in Post-Pandemic Engineering: Resilient Inclusive and Sustainable Actions", LACCEI 2022. 2022. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology). doi: 10.18687/LACCEI2022.1.1.578

Estrategia para la detección de tipos de enfermedades oculares usando red neuronal SOM

Resumen

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Conferencia

ODS de las Naciones Unidas

Palabras clave

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