Tuberculosis: Diagnosis by Image Processing

Authors

  • Wendy Morales Castro Universidad de Guanajuato
  • Rafael Guzman Cabrera Universidad de Guanajuato

DOI:

https://doi.org/10.13053/cys-24-2-3284

Keywords:

Tuberculosis detection, classification of medical images, medical diagnostic

Abstract

Tuberculosis is one of the first human diseases of which there is evidence, it´s very harmful and easy to spread through the air. One way to detect tuberculosis is by chest x-rays, by analyzing the x-ray you can obtain the detection of any abnormality (parenchymal, ganglionic or pleural). This paper presents a method that allows the presence of tuberculosis in medical X-ray images to be identified. Three methods of classification were implemented for the evaluation of the method: Support Vector Machine, Logistic Regression and K-Neighbors Classifier. Two classification scenarios were implemented: cross validation and training and test sets. The results obtained allow us to see the viability of the proposed method.

Author Biography

Rafael Guzman Cabrera, Universidad de Guanajuato

Profesor Titular BDepartamento de Ingenieria Electrica

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Published

2020-06-23

Issue

Vol. 24 No. 2 (2020): Thematic Issue on Language & Knowledge Engineering (Guest editors: D. Pinto, B. Beltrán, A. Vázquez)

Section

Articles

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