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Pneumonia Detection Using CNN based Feature Extraction
| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | K. Thakral A. Mittal D. Varshni R. Nijhawan L. Agarwal |
| Copyright Year | 2019 |
| Abstract | Pneumonia is a life-threatening infectious disease affecting one or both lungs in humans commonly caused by bacteria called Streptococcus pneumoniae. One in three deaths in India is caused due to pneumonia as reported by World Health Organization (WHO). Chest X-Rays which are used to diagnose pneumonia need expert radiotherapists for evaluation. Thus, developing an automatic system for detecting pneumonia would be beneficial for treating the disease without any delay particularly in remote areas. Due to the success of deep learning algorithms in analyzing medical images, Convolutional Neural Networks (CNNs) have gained much attention for disease classification. In addition, features learned by pre-trained CNN models on large-scale datasets are much useful in image classification tasks. In this work, we appraise the functionality of pre-trained CNN models utilized as feature-extractors followed by different classifiers for the classification of abnormal and normal chest X-Rays. We analytically determine the optimal CNN model for the purpose. Statistical results obtained demonstrates that pretrained CNN models employed along with supervised classifier algorithms can be very beneficial in analyzing chest X-ray images, specifically to detect Pneumonia. |
| Starting Page | 1 |
| Ending Page | 7 |
| Page Count | 7 |
| File Format | HTM / HTML |
| ISBN | 9781538681589 |
| Journal | 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT) |
| DOI | 10.1109/ICECCT.2019.8869364 |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Medical image processing Detecting pneumonia Transfer Learning Feature-extractors Cellular neural nets Lung Chest X-ray images X-rays Image classification tasks SVM Task analysis Random Forest Pretrained CNN models Microorganisms Deep Convolutional Neural Networks Optimal CNN model K-nearest neighbors Diagnostic radiography Pneumonia detection World Health Organization Convolutional Neural Networks Disease classification Diseases Streptococcus pneumoniae Support vector machines Abnormal chest X-Rays Naive Bayes Life-threatening infectious disease Deep learning algorithms Learning (artificial intelligence) Feature extraction Pre-trained CNN models DensetNet Convolutional neural networks Image classification |
| Content Type | Text |
| Resource Type | Preprint Article |
