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


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
Published in:	Industry, Innovation, and Infrastructure for Sustainable Cities and Communities: Proceedings of the 17th LACCEI International Multi-Conference for Engineering, Education and Technology
Date of Conference:	July 24-26, 2019
Location of Conference:	Montego Bay, Jamaica
Authors:	Marco Aedo Lopez (Universidad Nacional de San Agustín de Arequipa, PE) Eveling Gloria Castro Gutierrez (Universidad Nacional de San Agustín de Arequipa, PE) (Universidad Nacional de San Agustín de Arequipa)
Full Paper:	#395

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