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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
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← Back to VOLUME 10, ISSUE 6, JUNE 2021

Deep Learning For Detecting Pneumonia From X-ray Images

Vivek Abhange, Vishal Devershi, Raj Hode, Prof. V.S.Kolekar

DOI: 10.17148/IJARCCE.2021.10610

Abstract: The infection spreads in the lungs area of a human body. The chest x-ray is performed to diagnose this infection. Physicians use this X-ray image to diagnose or monitor treatment for conditions of pneumonia. This type of chest X-ray is also used in the diagnosis of diseases like emphysema, lung cancer, line and tube placement and tuberculosis. Feature extraction methods like DWT, WFT, and WPT can also be used. In this paper, detection of pneumonia infection by unsupervised fuzzy c-means classification learning algorithm is used. This approach gives better result than the rest of the methods. In fuzzy c-means, each resultant pixel gives accurate value since it has a weight associated with it.

Keywords: Deep learning · Chest CT scan · X-Ray Image · Cough analysis, radiomics, medical imaging, CNN, chest X-ray, neural networks,

How to Cite:

[1] Vivek Abhange, Vishal Devershi, Raj Hode, Prof. V.S.Kolekar, “Deep Learning For Detecting Pneumonia From X-ray Images,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2021.10610