Araştırma Makalesi
PDF Zotero Mendeley EndNote BibTex Kaynak Göster

Detection of Pneumonia with a Novel CNN-based Approach

Yıl 2021, Cilt 4, Sayı 1, 26 - 34, 30.04.2021
https://doi.org/10.35377/saucis.04.01.787030

Öz

Pneumonia is a seasonal infectious lung tissue inflammatory disease. According to the World Health Organization (WHO), early diagnosis of the disease reduces the risk of its transmission and death. Various deep learning and machine learning algorithms were used for pneumonia detection. This study aims to analyze the lung images and diagnose pneumonia disease by employing deep learning approaches. We have suggested a novel deep learning framework for the detection of pneumonia in lung. A comparison was made between the proposed new deep learning model and pre-trained deep learning models. 88.62% accuracy rate has been obtained from the proposed deep learning structure. It was observed that by utilizing the new deep neural network developed, the accuracy results of VGG16 (88.78%) and VGG19 (88.30%), which are among the popular deep learning architectures, can be approximated. The test results show that our proposed model has a better recall value (97.43%) (VGG16 (93.33%) and VGG19 (96.92%)), and a better F1-Score (91.45%) (VGG16 (91.22%) and VGG19 (91.19%)).

Kaynakça

  • K. He, G. Gkioxari, P. Dollar, and R. Girshick, "Mask r-cnn," in Proceedings of the IEEE international conference on computer vision., 2017.
  • T.-Y. Lin, P. Goyal, R. Girshick, K. He, and P. Dollar, "Focal loss for dense object detection," in Proceedings of the IEEE international conference on computer vision., 2017.
  • I. Sirazitdinov, M. Kholiavchenko, T. Mustafaev, Y. Yixuan, R. Kuleev, and B. Ibragimov, "Deep neural network ensemble for pneumonia localization from a large-scale chest x-ray database," Computers & Electrical Engineering., vol. 78, pp. 388-399, 2019.
  • Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, "Gradient-based learning applied to document recognition," Proceedings of the IEEE., vol. 86, no. 11, pp. 2278-2324, 1998.
  • Y. LeCun and Y. Bengio, "Convolutional networks for images, speech, and time series," The handbook of brain theory and neural networks., vol. 3361, no. 10, pp. 1995, 1995.
  • K. Simonyan, and A. Zisserman, "Very deep convolutional networks for large-scale image recognition," arXiv preprint arXiv:1409., vol. 1556, 2014.
  • F. Chollet, "Xception: Deep learning with depthwise separable convolutions," in Proceedings of the IEEE conference on computer vision and pattern recognition., 2017.
  • E. Ayan, and H.M. Ünver, "Diagnosis of Pneumonia from Chest X-Ray Images Using Deep Learning," in 2019 Scientific Meeting on Electrical-Electronics & Biomedical Engineering and Computer Science (EBBT)., 2019.
  • A. Krizhevsky, I. Sutskever, and G.E. Hinton, "Imagenet classification with deep convolutional neural networks," in Advances in neural information processing systems., 2012.
  • K. He, X. Zhang, S. Ren, and J. Sun, "Deep residual learning for image recognition," in Proceedings of the IEEE conference on computer vision and pattern recognition., 2016.
  • A. Bhandary, G.A. Prabhu, V. Rajinikanth, K.P. Thanaraj, S.C. Satapathy, D.E. Robbins, C. Shasky, Y.-D. Zhang, J.M.R.S. Tavares, and N.S.M. Raja, "Deep-learning framework to detect lung abnormality–A study with chest X-Ray and lung CT scan images," Pattern Recognition Letters., vol. 129, pp. 271-278, 2020.
  • G. Liang and L. Zheng, " A transfer learning method with deep residual network for pediatric pneumonia diagnosis," Computer methods and programs in biomedicine., vol. 187, pp. 104964, 2020.
  • V. Chouhan, S.K. Singh, A. Khamparia, D. Gupta, P. Tiwari, C. Moreira, R. Damasevicius, and V.H.C. de Albuquerque, "A Novel Transfer Learning Based Approach for Pneumonia Detection in Chest X-ray Images," Applied Sciences., vol. 10, no. 2, pp. 559, 2020.
  • R. Siddiqi, "Automated Pneumonia Diagnosis using a Customized Sequential Convolutional Neural Network," in Proceedings of the 2019 3rd International Conference on Deep Learning Technologies., 2019.
  • S.S. Yadav, S.M. Jadhav, "Deep convolutional neural network based medical image classification for disease diagnosis," J Big Data., vol. 6, pp. 113, 2019.
  • K.E. Asnaoui, Y. Chawki, and A. Idri, "Automated methods for detection and classification pneumonia based on x-ray images using deep learning," arXiv preprint arXiv:2003., pp. 14363, 2020.
  • A. Mittal, D. Kumar, M. Mittal, T. Saba, I. Abunadi, A. Rehman, and S. Roy, "Detecting Pneumonia Using Convolutions and Dynamic Capsule Routing for Chest X-ray Images," Sensors., vol. 20, no. 4, pp. 1068, 2020.
  • R. Jain, P. Nagrath, G. Kataria, V.S. Kaushik, and D.J. Hemanth, "Pneumonia detection in chest X-ray images using convolutional neural networks and transfer learning," Measurement., vol. 165, pp. 108046, 2020.
  • S. Chakraborty, S. Aich, J.S. Sim, and H.C. Kim, "Detection of pneumonia from chest x-rays using a convolutional neural network architecture," In International Conference on Future Information & Communication Engineering., vol. 11, no. 1, pp. 98-102, 2019.
  • D. Kermany, K. Zhang, and M. Goldbaum, "Labeled optical coherence tomography (oct) and chest X-ray images for classification," Mendeley data., vol. 2, 2018.
  • P. Mooney, "Chest X-Ray Images (Pneumonia)," 2017. [Online]. Available: https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia. [Accessed: 27-June-2020].
  • C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, Z. Wojna, "Rethinking the inception architecture for computer vision," in Proceedings of the IEEE conference on computer vision and pattern recognition., 2016.

Yıl 2021, Cilt 4, Sayı 1, 26 - 34, 30.04.2021
https://doi.org/10.35377/saucis.04.01.787030

Öz

Kaynakça

  • K. He, G. Gkioxari, P. Dollar, and R. Girshick, "Mask r-cnn," in Proceedings of the IEEE international conference on computer vision., 2017.
  • T.-Y. Lin, P. Goyal, R. Girshick, K. He, and P. Dollar, "Focal loss for dense object detection," in Proceedings of the IEEE international conference on computer vision., 2017.
  • I. Sirazitdinov, M. Kholiavchenko, T. Mustafaev, Y. Yixuan, R. Kuleev, and B. Ibragimov, "Deep neural network ensemble for pneumonia localization from a large-scale chest x-ray database," Computers & Electrical Engineering., vol. 78, pp. 388-399, 2019.
  • Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, "Gradient-based learning applied to document recognition," Proceedings of the IEEE., vol. 86, no. 11, pp. 2278-2324, 1998.
  • Y. LeCun and Y. Bengio, "Convolutional networks for images, speech, and time series," The handbook of brain theory and neural networks., vol. 3361, no. 10, pp. 1995, 1995.
  • K. Simonyan, and A. Zisserman, "Very deep convolutional networks for large-scale image recognition," arXiv preprint arXiv:1409., vol. 1556, 2014.
  • F. Chollet, "Xception: Deep learning with depthwise separable convolutions," in Proceedings of the IEEE conference on computer vision and pattern recognition., 2017.
  • E. Ayan, and H.M. Ünver, "Diagnosis of Pneumonia from Chest X-Ray Images Using Deep Learning," in 2019 Scientific Meeting on Electrical-Electronics & Biomedical Engineering and Computer Science (EBBT)., 2019.
  • A. Krizhevsky, I. Sutskever, and G.E. Hinton, "Imagenet classification with deep convolutional neural networks," in Advances in neural information processing systems., 2012.
  • K. He, X. Zhang, S. Ren, and J. Sun, "Deep residual learning for image recognition," in Proceedings of the IEEE conference on computer vision and pattern recognition., 2016.
  • A. Bhandary, G.A. Prabhu, V. Rajinikanth, K.P. Thanaraj, S.C. Satapathy, D.E. Robbins, C. Shasky, Y.-D. Zhang, J.M.R.S. Tavares, and N.S.M. Raja, "Deep-learning framework to detect lung abnormality–A study with chest X-Ray and lung CT scan images," Pattern Recognition Letters., vol. 129, pp. 271-278, 2020.
  • G. Liang and L. Zheng, " A transfer learning method with deep residual network for pediatric pneumonia diagnosis," Computer methods and programs in biomedicine., vol. 187, pp. 104964, 2020.
  • V. Chouhan, S.K. Singh, A. Khamparia, D. Gupta, P. Tiwari, C. Moreira, R. Damasevicius, and V.H.C. de Albuquerque, "A Novel Transfer Learning Based Approach for Pneumonia Detection in Chest X-ray Images," Applied Sciences., vol. 10, no. 2, pp. 559, 2020.
  • R. Siddiqi, "Automated Pneumonia Diagnosis using a Customized Sequential Convolutional Neural Network," in Proceedings of the 2019 3rd International Conference on Deep Learning Technologies., 2019.
  • S.S. Yadav, S.M. Jadhav, "Deep convolutional neural network based medical image classification for disease diagnosis," J Big Data., vol. 6, pp. 113, 2019.
  • K.E. Asnaoui, Y. Chawki, and A. Idri, "Automated methods for detection and classification pneumonia based on x-ray images using deep learning," arXiv preprint arXiv:2003., pp. 14363, 2020.
  • A. Mittal, D. Kumar, M. Mittal, T. Saba, I. Abunadi, A. Rehman, and S. Roy, "Detecting Pneumonia Using Convolutions and Dynamic Capsule Routing for Chest X-ray Images," Sensors., vol. 20, no. 4, pp. 1068, 2020.
  • R. Jain, P. Nagrath, G. Kataria, V.S. Kaushik, and D.J. Hemanth, "Pneumonia detection in chest X-ray images using convolutional neural networks and transfer learning," Measurement., vol. 165, pp. 108046, 2020.
  • S. Chakraborty, S. Aich, J.S. Sim, and H.C. Kim, "Detection of pneumonia from chest x-rays using a convolutional neural network architecture," In International Conference on Future Information & Communication Engineering., vol. 11, no. 1, pp. 98-102, 2019.
  • D. Kermany, K. Zhang, and M. Goldbaum, "Labeled optical coherence tomography (oct) and chest X-ray images for classification," Mendeley data., vol. 2, 2018.
  • P. Mooney, "Chest X-Ray Images (Pneumonia)," 2017. [Online]. Available: https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia. [Accessed: 27-June-2020].
  • C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, Z. Wojna, "Rethinking the inception architecture for computer vision," in Proceedings of the IEEE conference on computer vision and pattern recognition., 2016.

Ayrıntılar

Birincil Dil İngilizce
Konular Bilgisayar Bilimleri, Yapay Zeka
Bölüm Makaleler
Yazarlar

Ebru ERDEM (Sorumlu Yazar)
ATATURK UNIVERSITY
0000-0002-4042-7549
Türkiye


Tolga AYDİN
ATATURK UNIVERSITY
0000-0002-8971-3255
Türkiye

Yayımlanma Tarihi 30 Nisan 2021
Başvuru Tarihi 28 Ağustos 2020
Kabul Tarihi 28 Aralık 2020
Yayınlandığı Sayı Yıl 2021, Cilt 4, Sayı 1

Kaynak Göster

IEEE E. Erdem ve T. Aydin , "Detection of Pneumonia with a Novel CNN-based Approach", Sakarya University Journal of Computer and Information Sciences, c. 4, sayı. 1, ss. 26-34, Nis. 2021, doi:10.35377/saucis.04.01.787030