A novel tuberculosis diagnosis approach using feed-forward neural networks and binary pattern of phase congruency

A novel tuberculosis diagnosis approach using feed-forward neural networks and binary pattern of phase congruency

Tuberculosis is a severe and contagious lung disease that kills more than one million people annually, representing a real public health problem worldwide. Meanwhile, researchers and industry have highlighted the potential of analyzing and classifying chest radiographs (CXR) with artificial intellig...

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Bibliographic Details
Main Authors: Afonso Ueslei da Fonseca, Poliana Lopes Parreira, Gabriel da Silva Vieira, Juliana Paula Felix, Marcus Barreto Conte, Marcelo Fouad Rabahi, Fabrizzio Soares
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:Intelligent Systems with Applications
Subjects:
Artificial neural network
Tuberculosis detection
BPPC
FFNN
Chest radiograph
Online Access:http://www.sciencedirect.com/science/article/pii/S2667305323001424

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http://www.sciencedirect.com/science/article/pii/S2667305323001424

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