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

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

Research output: Contribution to journalArticlepeer-review

1 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 languageEnglish
Pages (from-to)989-997
Number of pages9
JournalComputacion y Sistemas
Volume24
Issue number3
DOIs
StatePublished - 2020
Externally publishedYes

Keywords

  • Artificial intelligence
  • Image processing
  • K-Means
  • Machine learning
  • SIFT algorithm

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