Detecting different stages of Alzheimer’s disease from MRI images using deep learning and computer vision techniques

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2024.

書誌詳細
主要な著者:	Rahman, Fardin, Sharif, Sadman, Islam, Syed Shams, Tirtho, Nihad Adnan Shah, Intheshar, Md. Ashir
その他の著者:	Karim, Dewan Ziaul
フォーマット:	学位論文
言語:	English
出版事項:	Brac University 2024
主題:	Machine learning Alzheimer Disease detection Convolutional neural network Neuroimaging Positron emission tomography Computer vision Neural networks (Computer science) Optical data processing Image processing > Digital techniques
オンライン･アクセス:	http://hdl.handle.net/10361/22870

id	10361-22870
record_format	dspace
spelling	10361-228702024-05-19T21:00:21Z Detecting different stages of Alzheimer’s disease from MRI images using deep learning and computer vision techniques Rahman, Fardin Sharif, Sadman Islam, Syed Shams Tirtho, Nihad Adnan Shah Intheshar, Md. Ashir Karim, Dewan Ziaul Department of Computer Science and Engineering, Brac University Machine learning Alzheimer Disease detection Convolutional neural network Neuroimaging Positron emission tomography Computer vision Neural networks (Computer science) Optical data processing Computer vision Image processing--Digital techniques This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2024. Cataloged from PDF version of thesis. Includes bibliographical references (pages 52-58). The preliminary and precise diagnosis of Alzheimer’s Disease is significant for the speedy management and intervention of the disorder. Numerous valuable tools such as Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET) etc. are used for evaluating the function and structure of brain which could help diagnose Alzheimer’s Disease. However, simplifying the MRI images manually is a hectic and long drawn process that is prone to observer variability. The prime prospect of this study is to employ a Computer Vision and Deep learning Based framework that would automatically classify the stage Alzheimer Disease (AD) through the MRI images. A large amount of dataset is used to enhance the effectiveness of the suggested structure. Moreover, this research demonstrates the capability of Computer vision and Deep learning in assisting premature AD detection. It provides a beneficial insight into the enrichment of neurological disease diagnosis using computer-aided technology. The highlight of this study is the introduction of a custom model that outperforms all state-of-the-art Convolutional Neural Network (CNN) models in performance. This novel model has achieved an exceptional accuracy of 96.6%, which showcases a meaningful advancement in the field and also provides a promising direction for future research in neurodegenerative disease diagnosis. Fardin Rahman Sadman Sharif Syed Shams Islam Nihad Adnan Shah Tirtho Md. Ashir Intheshar B.Sc in Computer Science and Engineering 2024-05-19T08:41:53Z 2024-05-19T08:41:53Z ©2024 2024-01 Thesis ID: 20101072 ID: 20101107 ID: 20301200 ID: 20101611 ID: 20101041 http://hdl.handle.net/10361/22870 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. 69 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Machine learning Alzheimer Disease detection Convolutional neural network Neuroimaging Positron emission tomography Computer vision Neural networks (Computer science) Optical data processing Computer vision Image processing--Digital techniques
spellingShingle	Machine learning Alzheimer Disease detection Convolutional neural network Neuroimaging Positron emission tomography Computer vision Neural networks (Computer science) Optical data processing Computer vision Image processing--Digital techniques Rahman, Fardin Sharif, Sadman Islam, Syed Shams Tirtho, Nihad Adnan Shah Intheshar, Md. Ashir Detecting different stages of Alzheimer’s disease from MRI images using deep learning and computer vision techniques
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2024.
author2	Karim, Dewan Ziaul
author_facet	Karim, Dewan Ziaul Rahman, Fardin Sharif, Sadman Islam, Syed Shams Tirtho, Nihad Adnan Shah Intheshar, Md. Ashir
format	Thesis
author	Rahman, Fardin Sharif, Sadman Islam, Syed Shams Tirtho, Nihad Adnan Shah Intheshar, Md. Ashir
author_sort	Rahman, Fardin
title	Detecting different stages of Alzheimer’s disease from MRI images using deep learning and computer vision techniques
title_short	Detecting different stages of Alzheimer’s disease from MRI images using deep learning and computer vision techniques
title_full	Detecting different stages of Alzheimer’s disease from MRI images using deep learning and computer vision techniques
title_fullStr	Detecting different stages of Alzheimer’s disease from MRI images using deep learning and computer vision techniques
title_full_unstemmed	Detecting different stages of Alzheimer’s disease from MRI images using deep learning and computer vision techniques
title_sort	detecting different stages of alzheimer’s disease from mri images using deep learning and computer vision techniques
publisher	Brac University
publishDate	2024
url	http://hdl.handle.net/10361/22870
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Detecting different stages of Alzheimer’s disease from MRI images using deep learning and computer vision techniques

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