Implementación de un modelo basado en técnicas de deep learning aplicado a la visión computacional en la clasificación de imágenes de rayos x, para el soporte del diagnóstico de lesiones traumatológicas de la estructura pélvica

Marco Wilfredo Aedo Lopez; Eveling Gloria Castro Gutierrez

doi:10.18687/LACCEI2019.1.1.395

Implementación de un modelo basado en técnicas de deep learning aplicado a la visión computacional en la clasificación de imágenes de rayos x, para el soporte del diagnóstico de lesiones traumatológicas de la estructura pélvica

Marco Wilfredo Aedo Lopez, Eveling Gloria Castro Gutierrez

Departamento Académico de Ingeniería de Sistemas e Informática

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

Resumen

This article describes the implementation of a model based on Deep Learning techniques applied to computational vision in the activity of classifying X-ray images as support in the diagnosis of traumatic lesions of the pelvic structure, specifically the acetabulum of the pelvis. In the area of Medical Sciences, nowadays, it is essential to have automated tools that support medical diagnosis. For the construction of these tools it is necessary to analyze the different techniques or methods provided by Computing, specifically Deep Learning, for the processing and interpretation of images and potentialize them with the application of GPUs to accelerate the achievement of results.

Título traducido de la contribución	Implementation of a model based on deep learning techniques applied to computer vision in the classification of x-ray images, for the support of the diagnosis of traumatological injuries of the pelvic structure
Idioma original	Español
Título de la publicación alojada	17th LACCEI International Multi-Conference for Engineering, Education, and Technology
Subtítulo de la publicación alojada	"Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019
Editorial	Latin American and Caribbean Consortium of Engineering Institutions
ISBN (versión digital)	9780999344361
DOI	https://doi.org/10.18687/LACCEI2019.1.1.395
Estado	Publicada - 2019
Evento	17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019 - Montego Bay, Jamaica Duración: 24 jul. 2019 → 26 jul. 2019

Serie de la publicación

Nombre	Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volumen	2019-July
ISSN (versión digital)	2414-6390

Conferencia

Conferencia	17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019
País/Territorio	Jamaica
Ciudad	Montego Bay
Período	24/07/19 → 26/07/19

Nota bibliográfica

Publisher Copyright:
© 2019 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.

Palabras clave

Computer Vision
Deep Learning
Pelvic structure
Pelvis Acetabulum
Traumatological injuries

Acceder al documento

10.18687/LACCEI2019.1.1.395

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Enlace a la publicación en Scopus

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Profundice en los temas de investigación de 'Implementación de un modelo basado en técnicas de deep learning aplicado a la visión computacional en la clasificación de imágenes de rayos x, para el soporte del diagnóstico de lesiones traumatológicas de la estructura pélvica'. En conjunto forman una huella única.

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Aedo Lopez, M. W., & Castro Gutierrez, E. G. (2019). Implementación de un modelo basado en técnicas de deep learning aplicado a la visión computacional en la clasificación de imágenes de rayos x, para el soporte del diagnóstico de lesiones traumatológicas de la estructura pélvica. En 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019 (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2019-July). Latin American and Caribbean Consortium of Engineering Institutions. https://doi.org/10.18687/LACCEI2019.1.1.395

Aedo Lopez, Marco Wilfredo ; Castro Gutierrez, Eveling Gloria. / Implementación de un modelo basado en técnicas de deep learning aplicado a la visión computacional en la clasificación de imágenes de rayos x, para el soporte del diagnóstico de lesiones traumatológicas de la estructura pélvica. 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019. Latin American and Caribbean Consortium of Engineering Institutions, 2019. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology).

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title = "Implementaci{\'o}n de un modelo basado en t{\'e}cnicas de deep learning aplicado a la visi{\'o}n computacional en la clasificaci{\'o}n de im{\'a}genes de rayos x, para el soporte del diagn{\'o}stico de lesiones traumatol{\'o}gicas de la estructura p{\'e}lvica",

abstract = "This article describes the implementation of a model based on Deep Learning techniques applied to computational vision in the activity of classifying X-ray images as support in the diagnosis of traumatic lesions of the pelvic structure, specifically the acetabulum of the pelvis. In the area of Medical Sciences, nowadays, it is essential to have automated tools that support medical diagnosis. For the construction of these tools it is necessary to analyze the different techniques or methods provided by Computing, specifically Deep Learning, for the processing and interpretation of images and potentialize them with the application of GPUs to accelerate the achievement of results.",

keywords = "Computer Vision, Deep Learning, Pelvic structure, Pelvis Acetabulum, Traumatological injuries",

author = "{Aedo Lopez}, {Marco Wilfredo} and {Castro Gutierrez}, {Eveling Gloria}",

note = "Publisher Copyright: {\textcopyright} 2019 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.; 17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019 ; Conference date: 24-07-2019 Through 26-07-2019",

year = "2019",

doi = "10.18687/LACCEI2019.1.1.395",

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

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

publisher = "Latin American and Caribbean Consortium of Engineering Institutions",

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Aedo Lopez, MW & Castro Gutierrez, EG 2019, Implementación de un modelo basado en técnicas de deep learning aplicado a la visión computacional en la clasificación de imágenes de rayos x, para el soporte del diagnóstico de lesiones traumatológicas de la estructura pélvica. En 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019. Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology, vol. 2019-July, Latin American and Caribbean Consortium of Engineering Institutions, 17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019, Montego Bay, Jamaica, 24/07/19. https://doi.org/10.18687/LACCEI2019.1.1.395

Implementación de un modelo basado en técnicas de deep learning aplicado a la visión computacional en la clasificación de imágenes de rayos x, para el soporte del diagnóstico de lesiones traumatológicas de la estructura pélvica. / Aedo Lopez, Marco Wilfredo ; Castro Gutierrez, Eveling Gloria.
17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019. Latin American and Caribbean Consortium of Engineering Institutions, 2019. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2019-July).

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

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AU - Castro Gutierrez, Eveling Gloria

PY - 2019

Y1 - 2019

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AB - This article describes the implementation of a model based on Deep Learning techniques applied to computational vision in the activity of classifying X-ray images as support in the diagnosis of traumatic lesions of the pelvic structure, specifically the acetabulum of the pelvis. In the area of Medical Sciences, nowadays, it is essential to have automated tools that support medical diagnosis. For the construction of these tools it is necessary to analyze the different techniques or methods provided by Computing, specifically Deep Learning, for the processing and interpretation of images and potentialize them with the application of GPUs to accelerate the achievement of results.

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Aedo Lopez MW , Castro Gutierrez EG. Implementación de un modelo basado en técnicas de deep learning aplicado a la visión computacional en la clasificación de imágenes de rayos x, para el soporte del diagnóstico de lesiones traumatológicas de la estructura pélvica. En 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019. Latin American and Caribbean Consortium of Engineering Institutions. 2019. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology). doi: 10.18687/LACCEI2019.1.1.395