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Predicting pneumonia and region detection from X-Ray images using deep neural network

Biomedical images are increasing drastically. Along the way, many machine learning algorithms have been proposed to predict and identify various kinds of diseases. One such disease is Pneumonia which is an infection caused by both bacteria and viruses through the inflammation of a person’s lung air...

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Main Authors: Sheikh Md, Hanif Hossain, S M, Raju, Ismail, Amelia Ritahani
Format: Article
Language:English
English
Published: 2021
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://irep.iium.edu.my/93859/1/93859_Predicting%20pneumonia%20and%20region%20detection.pdf
http://irep.iium.edu.my/93859/2/%5B2101.07717%5D%20Predicting%20Pneumonia%20and%20Region%20Detection%20from%20X-Ray%20Images%20using%20Deep%20Neural%20Network.pdf
http://irep.iium.edu.my/93859/
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spelling my.iium.irep.938592022-07-22T02:50:23Z http://irep.iium.edu.my/93859/ Predicting pneumonia and region detection from X-Ray images using deep neural network Sheikh Md, Hanif Hossain S M, Raju Ismail, Amelia Ritahani QA75 Electronic computers. Computer science Biomedical images are increasing drastically. Along the way, many machine learning algorithms have been proposed to predict and identify various kinds of diseases. One such disease is Pneumonia which is an infection caused by both bacteria and viruses through the inflammation of a person’s lung air sacs. In this paper, an algorithm was proposed that receives x-ray images as input and verifies whether this patient is infected by Pneumonia as well as specific region of the lungs that the inflammation has occurred at. The algorithm is based on the transfer learning mechanism where pretrained ResNet-50 (Convolutional Neural Network) was used followed by some custom layer for making the prediction. The model has achieved an accuracy of 90.6 percent which confirms that the model is effective and can be implemented for the detection of Pneumonia in patients. Furthermore, a class activation map is used for the detection of the infected region in the lungs. Also, PneuNet was developed so that users can access more easily and use the services. 2021-01 Article PeerReviewed application/pdf en http://irep.iium.edu.my/93859/1/93859_Predicting%20pneumonia%20and%20region%20detection.pdf application/pdf en http://irep.iium.edu.my/93859/2/%5B2101.07717%5D%20Predicting%20Pneumonia%20and%20Region%20Detection%20from%20X-Ray%20Images%20using%20Deep%20Neural%20Network.pdf Sheikh Md, Hanif Hossain and S M, Raju and Ismail, Amelia Ritahani (2021) Predicting pneumonia and region detection from X-Ray images using deep neural network. eprint arXiv:2101.07717.
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Sheikh Md, Hanif Hossain
S M, Raju
Ismail, Amelia Ritahani
Predicting pneumonia and region detection from X-Ray images using deep neural network
description Biomedical images are increasing drastically. Along the way, many machine learning algorithms have been proposed to predict and identify various kinds of diseases. One such disease is Pneumonia which is an infection caused by both bacteria and viruses through the inflammation of a person’s lung air sacs. In this paper, an algorithm was proposed that receives x-ray images as input and verifies whether this patient is infected by Pneumonia as well as specific region of the lungs that the inflammation has occurred at. The algorithm is based on the transfer learning mechanism where pretrained ResNet-50 (Convolutional Neural Network) was used followed by some custom layer for making the prediction. The model has achieved an accuracy of 90.6 percent which confirms that the model is effective and can be implemented for the detection of Pneumonia in patients. Furthermore, a class activation map is used for the detection of the infected region in the lungs. Also, PneuNet was developed so that users can access more easily and use the services.
format Article
author Sheikh Md, Hanif Hossain
S M, Raju
Ismail, Amelia Ritahani
author_facet Sheikh Md, Hanif Hossain
S M, Raju
Ismail, Amelia Ritahani
author_sort Sheikh Md, Hanif Hossain
title Predicting pneumonia and region detection from X-Ray images using deep neural network
title_short Predicting pneumonia and region detection from X-Ray images using deep neural network
title_full Predicting pneumonia and region detection from X-Ray images using deep neural network
title_fullStr Predicting pneumonia and region detection from X-Ray images using deep neural network
title_full_unstemmed Predicting pneumonia and region detection from X-Ray images using deep neural network
title_sort predicting pneumonia and region detection from x-ray images using deep neural network
publishDate 2021
url http://irep.iium.edu.my/93859/1/93859_Predicting%20pneumonia%20and%20region%20detection.pdf
http://irep.iium.edu.my/93859/2/%5B2101.07717%5D%20Predicting%20Pneumonia%20and%20Region%20Detection%20from%20X-Ray%20Images%20using%20Deep%20Neural%20Network.pdf
http://irep.iium.edu.my/93859/
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score 13.211869

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