Tuberculosis detection architecture with image processing using the SIFT and K-means algorithm

Hugo D. Calderon Vilca; Luis M. Ortega Melgarejo; Guido R. Larico Uchamaco; Flor C. Cárdenas Mariño

doi:10.13053/CyS-24-3-3120

Tuberculosis detection architecture with image processing using the SIFT and K-means algorithm

Hugo D. Calderon Vilca, Luis M. Ortega Melgarejo, Guido R. Larico Uchamaco, Flor C. Cárdenas Mariño

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

Tuberculosis is a lethal disease that attacks the lungs in a similar way to COVID 19, according to the who, until 2018 there were more than 10 million people infected with tuberculosis and 1.5 million died with this disease. Artificial Intelligence algorithms allow detecting these diseases quickly and massively. We present an architecture to detect tuberculosis with image processing on lung radiographs, using the SIFT and K-means algorithms. We have tested the architecture with 300 radiographs, achieving 90.3% accuracy in classification.

Original language	English
Pages (from-to)	989-997
Number of pages	9
Journal	Computacion y Sistemas
Volume	24
Issue number	3
DOIs	https://doi.org/10.13053/CyS-24-3-3120
State	Published - 2020
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2020 Instituto Politecnico Nacional. All rights reserved.

Keywords

Artificial intelligence
Image processing
K-Means
Machine learning
SIFT algorithm

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10.13053/CyS-24-3-3120

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abstract = "Tuberculosis is a lethal disease that attacks the lungs in a similar way to COVID 19, according to the who, until 2018 there were more than 10 million people infected with tuberculosis and 1.5 million died with this disease. Artificial Intelligence algorithms allow detecting these diseases quickly and massively. We present an architecture to detect tuberculosis with image processing on lung radiographs, using the SIFT and K-means algorithms. We have tested the architecture with 300 radiographs, achieving 90.3% accuracy in classification.",

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AU - Calderon Vilca, Hugo D.

AU - Ortega Melgarejo, Luis M.

AU - Larico Uchamaco, Guido R.

AU - Cárdenas Mariño, Flor C.

PY - 2020

Y1 - 2020

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AB - Tuberculosis is a lethal disease that attacks the lungs in a similar way to COVID 19, according to the who, until 2018 there were more than 10 million people infected with tuberculosis and 1.5 million died with this disease. Artificial Intelligence algorithms allow detecting these diseases quickly and massively. We present an architecture to detect tuberculosis with image processing on lung radiographs, using the SIFT and K-means algorithms. We have tested the architecture with 300 radiographs, achieving 90.3% accuracy in classification.

KW - Artificial intelligence

KW - Image processing

KW - K-Means

KW - Machine learning

KW - SIFT algorithm

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Tuberculosis detection architecture with image processing using the SIFT and K-means algorithm

Abstract

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Keywords

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