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...
| Main Authors: | , , , , , |
|---|---|
| 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 |
| _version_ | 1825951387683389440 |
|---|---|
| author | Meraj, Syeda Shaizadi Yaakob, Razali Azman, Azreen Mohd Rum, Siti Nurulain Ahmad Nazri, Azree Shahrel Zakaria, Nor Fadhlina |
| 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 |
| collection | UPM |
| 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. |
| first_indexed | 2024-03-06T10:29:16Z |
| format | Article |
| id | upm.eprints-81112 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:29:16Z |
| publishDate | 2019 |
| publisher | Blue Eyes Intelligence Engineering & Sciences Publication |
| record_format | dspace |
| spelling | 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 |
| 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 |
| title | 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_short | 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 |
| url | http://psasir.upm.edu.my/id/eprint/81112/1/TUBER.pdf |
| work_keys_str_mv | AT merajsyedashaizadi detectionofpulmonarytuberculosismanifestationinchestxraysusingdifferentconvolutionalneuralnetworkcnnmodels AT yaakobrazali detectionofpulmonarytuberculosismanifestationinchestxraysusingdifferentconvolutionalneuralnetworkcnnmodels AT azmanazreen detectionofpulmonarytuberculosismanifestationinchestxraysusingdifferentconvolutionalneuralnetworkcnnmodels AT mohdrumsitinurulain detectionofpulmonarytuberculosismanifestationinchestxraysusingdifferentconvolutionalneuralnetworkcnnmodels AT ahmadnazriazreeshahrel detectionofpulmonarytuberculosismanifestationinchestxraysusingdifferentconvolutionalneuralnetworkcnnmodels AT zakarianorfadhlina detectionofpulmonarytuberculosismanifestationinchestxraysusingdifferentconvolutionalneuralnetworkcnnmodels |