A Deep Convolutional Neural Network Based Lung Disorder Diagnosis

Authors

  • J. Juditha Mercina  Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
  • J. Madhumathi  Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
  • V. Priyanga  Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
  • M. Deva Priya  Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India

DOI:

https://doi.org//10.32628/CSEIT19525

Keywords:

Convolution Neural Networks, X-Ray, Lung Diseases, Keras, Softmax Accuracy, Confidence, Confusion Matrix, Training, Testing

Abstract

Lungs play an important role in human respiratory system. There are diseases that affect the functioning of lungs. To analyse lung diseases in the chest region using X-ray based Computer-Aided Diagnosis (CAD) system, it is necessary to determine the lung regions subject to analysis. In this paper, an intelligent system is proposed for lung disease detection. In this paper, Interstitial Lung Disease (ILD) patterns are classified using Convolutional Neural Networks (CNN). The proposed system involves five convolutional layers and three dense layers. The performance of the classification demonstrates the potential of CNN in analysing lung patterns.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2019-04-30

Issue

Volume 5, Issue 2, March-April-2019

Section

Research Articles

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How to Cite

[1]
J. Juditha Mercina, J. Madhumathi, V. Priyanga, M. Deva Priya, " A Deep Convolutional Neural Network Based Lung Disorder Diagnosis, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.102-112, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT19525