Detection of pneumonia from chest X-ray images using machine learning
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.
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Brac University
2023
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10361-220112023-12-20T21:02:41Z Detection of pneumonia from chest X-ray images using machine learning Priya, Afsana Rahman Sarkar, Kashmira Khan, Tania Rahman Turna, Sohani Fatehin Mubashshira, Sadia Karim, Dewan Ziaul Department of Computer Science and Engineering, Brac University X-ray images Computer-based algorithm Customized CNN model Pre-trained models VGG-16 Inceptionv3 ResNet50 VGG-19 Accuracy F1-Score Machine learning Neural networks (Computer science) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023. Cataloged from PDF version of thesis. Includes bibliographical references (pages 36-37). A bacterial infection is the cause of the lung condition known as pneumonia. An essential component of a successful treatment procedure is early diagnosis. Without early diagnosis, pneumonia can be severe or even can cause death. Viewing X-ray images is one of the ways to detect pneumonia. For accurate viewing or reading of X-ray images, a computer-based algorithm is preferable over reading X-ray images manually. In this study, a pneumonia detection system is created using grounded feature extraction from convolutional neural networks (CNN). To predict the occurrence of pneumonia, different classification algorithm models are used. For classi-fication, customized CNN models and various pre-trained models such as VGG-16, Inceptionv3, ResNet50, and VGG-19 are applied to the x-ray image dataset. After implementing all these models we obtained our best accuracy from the Customized CNN model which is 90.43% and the best f1-score from Customized CNN, ResNet50, and VGG-19, the score is 0.87. Afsana Rahman Priya Kashmira Sarkar Tania Rahman Khan Sohani Fatehin Turna Sadia Mubashshira B.Sc. in Computer Science and Engineering 2023-12-20T04:35:12Z 2023-12-20T04:35:12Z 2023 2023-05 Thesis ID 19301181 ID 19101139 ID 19101513 ID 19301132 ID 19101664 http://hdl.handle.net/10361/22011 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 37 pages application/pdf Brac University |
institution |
Brac University |
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Institutional Repository |
language |
English |
topic |
X-ray images Computer-based algorithm Customized CNN model Pre-trained models VGG-16 Inceptionv3 ResNet50 VGG-19 Accuracy F1-Score Machine learning Neural networks (Computer science) |
spellingShingle |
X-ray images Computer-based algorithm Customized CNN model Pre-trained models VGG-16 Inceptionv3 ResNet50 VGG-19 Accuracy F1-Score Machine learning Neural networks (Computer science) Priya, Afsana Rahman Sarkar, Kashmira Khan, Tania Rahman Turna, Sohani Fatehin Mubashshira, Sadia Detection of pneumonia from chest X-ray images using machine learning |
description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023. |
author2 |
Karim, Dewan Ziaul |
author_facet |
Karim, Dewan Ziaul Priya, Afsana Rahman Sarkar, Kashmira Khan, Tania Rahman Turna, Sohani Fatehin Mubashshira, Sadia |
format |
Thesis |
author |
Priya, Afsana Rahman Sarkar, Kashmira Khan, Tania Rahman Turna, Sohani Fatehin Mubashshira, Sadia |
author_sort |
Priya, Afsana Rahman |
title |
Detection of pneumonia from chest X-ray images using machine learning |
title_short |
Detection of pneumonia from chest X-ray images using machine learning |
title_full |
Detection of pneumonia from chest X-ray images using machine learning |
title_fullStr |
Detection of pneumonia from chest X-ray images using machine learning |
title_full_unstemmed |
Detection of pneumonia from chest X-ray images using machine learning |
title_sort |
detection of pneumonia from chest x-ray images using machine learning |
publisher |
Brac University |
publishDate |
2023 |
url |
http://hdl.handle.net/10361/22011 |
work_keys_str_mv |
AT priyaafsanarahman detectionofpneumoniafromchestxrayimagesusingmachinelearning AT sarkarkashmira detectionofpneumoniafromchestxrayimagesusingmachinelearning AT khantaniarahman detectionofpneumoniafromchestxrayimagesusingmachinelearning AT turnasohanifatehin detectionofpneumoniafromchestxrayimagesusingmachinelearning AT mubashshirasadia detectionofpneumoniafromchestxrayimagesusingmachinelearning |
_version_ |
1814307370359062528 |