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Detection of pulmonary tuberculosis manifestation in chest x-rays using different Convolutional Neural Network (CNN) models

Tuberculosis (TB) is airborne infectious disease which has claimed many lives than any other infectious disease. Chest X-rays (CXRs) are often used in recognizing TB manifestation site in chest. Lately, CXRs are taken in digital formats, which has made a huge impact in rapid diagnosis using automate...

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Main Authors: Meraj, Syeda Shaizadi, Yaakob, Razali, Azman, Azreen, Mohd Rum, Siti Nurulain, Ahmad Nazri, Azree Shahrel, Zakaria, Nor Fadhlina
Format: Article
Language:English
Published: Blue Eyes Intelligence Engineering & Sciences Publication 2019
Online Access:http://psasir.upm.edu.my/id/eprint/81112/1/TUBER.pdf
http://psasir.upm.edu.my/id/eprint/81112/
https://www.ijeat.org/wp-content/uploads/papers/v9i1/A2632109119.pdf
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spelling my.upm.eprints.811122020-10-14T21:10:57Z http://psasir.upm.edu.my/id/eprint/81112/ Detection of pulmonary tuberculosis manifestation in chest x-rays using different Convolutional Neural Network (CNN) models Meraj, Syeda Shaizadi Yaakob, Razali Azman, Azreen Mohd Rum, Siti Nurulain Ahmad Nazri, Azree Shahrel Zakaria, Nor Fadhlina Tuberculosis (TB) is airborne infectious disease which has claimed many lives than any other infectious disease. Chest X-rays (CXRs) are often used in recognizing TB manifestation site in chest. Lately, CXRs are taken in digital formats, which has made a huge impact in rapid diagnosis using automated systems in medical field. In our current work, four simple Convolutional Neural Networks (CNN) models such as VGG-16, VGG-19, RestNet50, and GoogLenet are implemented in identification of TB manifested CXRs. Two public TB image datasets were utilized to conduct this research. This study was carried out to explore the limit of accuracies and AUCs acquired by simple and small-scale CNN with complex and large-scale CNN models. The results achieved from this work are compared with results of two previous studies. The results indicate that our proposed VGG-16 model has gained highest score overall compared to the models from other two previous studies. Blue Eyes Intelligence Engineering & Sciences Publication 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/81112/1/TUBER.pdf Meraj, Syeda Shaizadi and Yaakob, Razali and Azman, Azreen and Mohd Rum, Siti Nurulain and Ahmad Nazri, Azree Shahrel and Zakaria, Nor Fadhlina (2019) Detection of pulmonary tuberculosis manifestation in chest x-rays using different Convolutional Neural Network (CNN) models. International Journal of Engineering and Advanced Technology, 9 (1). pp. 2270-2275. ISSN 2249-8958 https://www.ijeat.org/wp-content/uploads/papers/v9i1/A2632109119.pdf 10.35940/ijeat.A2632.109119
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Tuberculosis (TB) is airborne infectious disease which has claimed many lives than any other infectious disease. Chest X-rays (CXRs) are often used in recognizing TB manifestation site in chest. Lately, CXRs are taken in digital formats, which has made a huge impact in rapid diagnosis using automated systems in medical field. In our current work, four simple Convolutional Neural Networks (CNN) models such as VGG-16, VGG-19, RestNet50, and GoogLenet are implemented in identification of TB manifested CXRs. Two public TB image datasets were utilized to conduct this research. This study was carried out to explore the limit of accuracies and AUCs acquired by simple and small-scale CNN with complex and large-scale CNN models. The results achieved from this work are compared with results of two previous studies. The results indicate that our proposed VGG-16 model has gained highest score overall compared to the models from other two previous studies.
format Article
author Meraj, Syeda Shaizadi
Yaakob, Razali
Azman, Azreen
Mohd Rum, Siti Nurulain
Ahmad Nazri, Azree Shahrel
Zakaria, Nor Fadhlina
spellingShingle Meraj, Syeda Shaizadi
Yaakob, Razali
Azman, Azreen
Mohd Rum, Siti Nurulain
Ahmad Nazri, Azree Shahrel
Zakaria, Nor Fadhlina
Detection of pulmonary tuberculosis manifestation in chest x-rays using different Convolutional Neural Network (CNN) models
author_facet Meraj, Syeda Shaizadi
Yaakob, Razali
Azman, Azreen
Mohd Rum, Siti Nurulain
Ahmad Nazri, Azree Shahrel
Zakaria, Nor Fadhlina
author_sort Meraj, Syeda Shaizadi
title Detection of pulmonary tuberculosis manifestation in chest x-rays using different Convolutional Neural Network (CNN) models
title_short Detection of pulmonary tuberculosis manifestation in chest x-rays using different Convolutional Neural Network (CNN) models
title_full Detection of pulmonary tuberculosis manifestation in chest x-rays using different Convolutional Neural Network (CNN) models
title_fullStr Detection of pulmonary tuberculosis manifestation in chest x-rays using different Convolutional Neural Network (CNN) models
title_full_unstemmed Detection of pulmonary tuberculosis manifestation in chest x-rays using different Convolutional Neural Network (CNN) models
title_sort detection of pulmonary tuberculosis manifestation in chest x-rays using different convolutional neural network (cnn) models
publisher Blue Eyes Intelligence Engineering & Sciences Publication
publishDate 2019
url http://psasir.upm.edu.my/id/eprint/81112/1/TUBER.pdf
http://psasir.upm.edu.my/id/eprint/81112/
https://www.ijeat.org/wp-content/uploads/papers/v9i1/A2632109119.pdf
_version_ 1681490846887706624
score 13.211869

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