Detection of skin cancer 'Melanoma' through computer vision

Wilson F. Cueva; F. Munoz; G. Vasquez; G. Delgado

doi:10.1109/INTERCON.2017.8079674

Detection of skin cancer 'Melanoma' through computer vision

Wilson F. Cueva, F. Munoz, G. Vasquez, G. Delgado

Universidad del Azuay

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

20 Citas (Scopus)

Resumen

In the last decades, skin cancer increased its incidence becoming a public health problem. Technological advances have allowed the development of applications that help the early detection of melanoma. In this context, an image processing was developed to obtain Asymmetry, Border, Color, and Diameter (ABCD of melanoma). Using neural networks to perform a classification of the different kinds of moles. As a result, this algorithm developed after an analysis of 200 images was obtained a performance of 97.51%.

Idioma original	Inglés
Título de la publicación alojada	Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017
Editorial	Institute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)	9781509063628
DOI	https://doi.org/10.1109/INTERCON.2017.8079674
Estado	Publicada - 20 oct. 2017
Publicado de forma externa	Sí
Evento	24th IEEE International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017 - Cusco, Perú Duración: 15 ago. 2017 → 18 ago. 2017

Serie de la publicación

Nombre	Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017

Conferencia

Conferencia	24th IEEE International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017
País/Territorio	Perú
Ciudad	Cusco
Período	15/08/17 → 18/08/17

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

Acceder al documento

10.1109/INTERCON.2017.8079674

Otros archivos y enlaces

Enlace a la publicación en Scopus

Citar esto

Cueva, W. F., Munoz, F., Vasquez, G., & Delgado, G. (2017). Detection of skin cancer 'Melanoma' through computer vision. En Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017 Artículo 8079674 (Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INTERCON.2017.8079674

Cueva, Wilson F. ; Munoz, F. ; Vasquez, G. et al. / Detection of skin cancer 'Melanoma' through computer vision. Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017. Institute of Electrical and Electronics Engineers Inc., 2017. (Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017).

@inproceedings{67eb8ba9085c4ea684297a9e311ba712,

title = "Detection of skin cancer 'Melanoma' through computer vision",

abstract = "In the last decades, skin cancer increased its incidence becoming a public health problem. Technological advances have allowed the development of applications that help the early detection of melanoma. In this context, an image processing was developed to obtain Asymmetry, Border, Color, and Diameter (ABCD of melanoma). Using neural networks to perform a classification of the different kinds of moles. As a result, this algorithm developed after an analysis of 200 images was obtained a performance of 97.51\%.",

keywords = "Artificial Intelligence, Image Processing, Melanoma, Neural Networks",

author = "Cueva, \{Wilson F.\} and F. Munoz and G. Vasquez and G. Delgado",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 24th IEEE International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017 ; Conference date: 15-08-2017 Through 18-08-2017",

year = "2017",

month = oct,

day = "20",

doi = "10.1109/INTERCON.2017.8079674",

language = "Ingl{\'e}s",

series = "Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017",

}

Cueva, WF, Munoz, F, Vasquez, G & Delgado, G 2017, Detection of skin cancer 'Melanoma' through computer vision. En Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017., 8079674, Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017, Institute of Electrical and Electronics Engineers Inc., 24th IEEE International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017, Cusco, Perú, 15/08/17. https://doi.org/10.1109/INTERCON.2017.8079674

Detection of skin cancer 'Melanoma' through computer vision. / Cueva, Wilson F.; Munoz, F.; Vasquez, G. et al.
Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 8079674 (Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017).

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

TY - GEN

T1 - Detection of skin cancer 'Melanoma' through computer vision

AU - Cueva, Wilson F.

AU - Munoz, F.

AU - Vasquez, G.

AU - Delgado, G.

PY - 2017/10/20

Y1 - 2017/10/20

N2 - In the last decades, skin cancer increased its incidence becoming a public health problem. Technological advances have allowed the development of applications that help the early detection of melanoma. In this context, an image processing was developed to obtain Asymmetry, Border, Color, and Diameter (ABCD of melanoma). Using neural networks to perform a classification of the different kinds of moles. As a result, this algorithm developed after an analysis of 200 images was obtained a performance of 97.51%.

AB - In the last decades, skin cancer increased its incidence becoming a public health problem. Technological advances have allowed the development of applications that help the early detection of melanoma. In this context, an image processing was developed to obtain Asymmetry, Border, Color, and Diameter (ABCD of melanoma). Using neural networks to perform a classification of the different kinds of moles. As a result, this algorithm developed after an analysis of 200 images was obtained a performance of 97.51%.

KW - Artificial Intelligence

KW - Image Processing

KW - Melanoma

KW - Neural Networks

UR - https://www.scopus.com/pages/publications/85039989899

U2 - 10.1109/INTERCON.2017.8079674

DO - 10.1109/INTERCON.2017.8079674

M3 - Contribución a la conferencia

AN - SCOPUS:85039989899

T3 - Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017

BT - Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 24th IEEE International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017

Y2 - 15 August 2017 through 18 August 2017

ER -

Cueva WF, Munoz F, Vasquez G, Delgado G. Detection of skin cancer 'Melanoma' through computer vision. En Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017. Institute of Electrical and Electronics Engineers Inc. 2017. 8079674. (Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017). doi: 10.1109/INTERCON.2017.8079674

Detection of skin cancer 'Melanoma' through computer vision

Resumen

Serie de la publicación

Conferencia

ODS de las Naciones Unidas

Acceder al documento

Otros archivos y enlaces

Huella

Citar esto