LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN
Abstract & Details
Research Area
Computer Engineering
Keywords
Pneumonia
diagnosis
cardiomegaly
tomography
CXR
CNN
Abstract
Pneumonia is a life-threatening infectious disease affecting one or both lungs in humans commonly caused by bacteria called Streptococcus pneumonia. COVID19 can cause severe pneumonia and is estimated to have a high impact on the healthcare system. Early diagnosis is crucial for the correct treatment to possibly reduce the stress in the healthcare system. Pneumonia has caused significant deaths worldwide, and it is a challenging task to detect many lung diseases such as atelectasis, cardiomegaly, lung cancer, etc., often due to limited professional radiologists in hospital settings. The standard image diagnosis tests for pneumonia are chest X-ray (CXR) and computed tomography (CT) scan. Although CT scan is the gold standard, CXR is still useful because it is cheaper, faster, and more widespread. 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 and it can save lots of people's lives and help to stop and cure, control a treat 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 demonstrate that pre-trained CNN models employed along with supervised classifier algorithms can be very beneficial in analyzing chest X-ray images, specifically to detect Pneumonia. This study aims to identify pneumonia caused by other types and also healthy lungs using only X-Ray images. Keywords: X-Ray, CXR, COVID-19, Chest X-ray images, pneumonia detection; convolutional network (CNN), image enhancement.
License
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Commons
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Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Sakshi K. Jadhav | Sir Visvesvaraya Institute of Technology, Nashik |
| 2 | Khan Mohommad Faraaz Firoz | Sir Visvesvaraya Institute of Technology, Nashik |
| 3 | Khan Mohd Afraaz Firoz | Sir Visvesvaraya Institute of Technology, Nashik |
| 4 | Rushikesh S. Ohol | Sir Visvesvaraya Institute of Technology, Nashik |
| 5 | Prof. Uttam R. Patole | Sir Visvesvaraya Institute of Technology, Nashik |
How to Cite
Use the following formats to cite this article in your research.
APA Style
Jadhav, Sakshi K., Firoz, Khan Mohommad Faraaz, Firoz, Khan Mohd Afraaz, Ohol, Rushikesh S., & Patole, Prof. Uttam R. (2022). LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN. International Journal of Advance Research and Innovative Ideas In Education, 8(3), 2024-2029.
MLA Style
Jadhav, Sakshi K., et al. "LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN." International Journal of Advance Research and Innovative Ideas In Education, vol. 8, no. 3, 2022, pp. 2024-2029.
IEEE Style
Sakshi K. Jadhav, Khan Mohommad Faraaz Firoz, Khan Mohd Afraaz Firoz, Rushikesh S. Ohol, and Prof. Uttam R. Patole, "LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN," International Journal of Advance Research and Innovative Ideas In Education, vol. 8, no. 3, pp. 2024-2029, 2022.
Vancouver Style
Jadhav Sakshi K., Firoz Khan Mohommad Faraaz, Firoz Khan Mohd Afraaz, Ohol Rushikesh S., Patole Prof. Uttam R.. LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN. International Journal of Advance Research and Innovative Ideas In Education. 2022;8(3):2024-2029.
Harvard Style
Jadhav, Sakshi K., Firoz, Khan Mohommad Faraaz, Firoz, Khan Mohd Afraaz, Ohol, Rushikesh S., & Patole, Prof. Uttam R. (2022) 'LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN', International Journal of Advance Research and Innovative Ideas In Education, 8(3), pp. 2024-2029.
Chicago Style
Jadhav, Sakshi K., et al. "LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN." International Journal of Advance Research and Innovative Ideas In Education 8, no. 3 (2022): 2024-2029.
Turabian Style
Jadhav, Sakshi K., et al. "LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN." International Journal of Advance Research and Innovative Ideas In Education 8, no. 3 (2022): 2024-2029.
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