TY - JOUR
T1 - Tuberculosis detection architecture with image processing using the SIFT and K-means algorithm
AU - Calderon Vilca, Hugo D.
AU - Ortega Melgarejo, Luis M.
AU - Larico Uchamaco, Guido R.
AU - Cárdenas Mariño, Flor C.
N1 - Publisher Copyright:
© 2020 Instituto Politecnico Nacional. All rights reserved.
PY - 2020
Y1 - 2020
N2 - 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.
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
UR - http://www.scopus.com/inward/record.url?scp=85094914265&partnerID=8YFLogxK
U2 - 10.13053/CyS-24-3-3120
DO - 10.13053/CyS-24-3-3120
M3 - Artículo
AN - SCOPUS:85094914265
SN - 1405-5546
VL - 24
SP - 989
EP - 997
JO - Computacion y Sistemas
JF - Computacion y Sistemas
IS - 3
ER -