Preliminary Screening for Pulmonary Tuberculosis from Chest Radiography using Artificial Neural Network

Preliminary Screening for Pulmonary Tuberculosis from Chest Radiography using Artificial Neural Network
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© 2022 by IJETT Journal
Volume-70 Issue-8
Year of Publication : 2022
Authors : Sucheera Phramala, Weeragul Pratumgul, Jagraphon obma, Worawat Sa-ngiamvibool
DOI : 10.14445/22315381/IJETT-V70I8P233

How to Cite?

Sucheera Phramala, Weeragul Pratumgul, Jagraphon obma, Worawat Sa-ngiamvibool, "Preliminary Screening for Pulmonary Tuberculosis from Chest Radiography using Artificial Neural Network," International Journal of Engineering Trends and Technology, vol. 70, no. 8, pp. 318-326, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I8P233

Abstract
This research has developed an algorithm for primary screening of pulmonary tuberculosis from chest radiographs by using the image processing principle with Artificial Neural Network (ANN) to examine the preliminary features related to the high incidence of pulmonary tuberculosis, namely Reticular Infiltration, Cavity, and Consolidation. The procedure was then used to learn 14,000 chest radiographs and tested for preliminary screening on 6,000 test images. The test result found that this method can process with an accuracy of 82.20%, a sensitivity of 86.80%, specificity of 79.59% and positive predictive values of 77.37% compared with the radiologist.

Keywords
Chest radiography, Artificial neural network, Image processing, Pulmonary tuberculosis.

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