An efficient deep learning approach for detecting Alzheimer’s disease using brain images

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.

Bibliographic Details
Main Authors:	Sani, Mehedi Hasan, Rahman, Mohibur, Achib, Md. Abdullah Al, Hossain, Rakib
Other Authors:	Alam, Md. Ashraful
Format:	Thesis
Language:	English
Published:	Brac University 2022
Subjects:	CNN Deep learning VGG-19 Resnet-101 Inception v3 MRI image classification Detecting Alzheimer disease Cognitive learning theory (Deep learning) Alzheimer's disease. Neural networks (Computer science) Brain > Imaging > Mathematical models.
Online Access:	http://hdl.handle.net/10361/16906

id	10361-16906
record_format	dspace
spelling	10361-169062022-06-06T21:01:32Z An efficient deep learning approach for detecting Alzheimer’s disease using brain images Sani, Mehedi Hasan Rahman, Mohibur Achib, Md. Abdullah Al Hossain, Rakib Alam, Md. Ashraful Department of Computer Science and Engineering, Brac University CNN Deep learning VGG-19 Resnet-101 Inception v3 MRI image classification Detecting Alzheimer disease Cognitive learning theory (Deep learning) Alzheimer's disease. Neural networks (Computer science) Brain -- Imaging -- Mathematical models. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 29-30). Alzheimer’s disease (AD) is a disorder of the brain which causes the loss of memory. This is a successively growing disease which means the severity of it will be upward with the time. In this century, AD is one of the major concerns in the medical arena. The objective of our work is to improve a system that will be able to detect the disease at an early stage. We used efficient deep learning for our project as nowadays, deep learning plays a vital role in every research field. We used MRI of brain for our project using which, our model can identify whether there is sign of Alzheimer’s disease or not. Besides, our model is multiclass classification related which means it can work on different stages of AD.We used different architectures of Convolutional Neural Network (CNN) that are VGG-19, Inception V3 and ResNet- 101 and the accuracy we attained from our models are 88.02%, 89.62% and 91.49% respectively which are pretty decent scores. Since it is an irreversible disorder, we can perceive the significance of detecting the disease at an early stage with good accuracy. Thus, we can state based on the performance of our models that these might play some important role to detect AD. Mehedi Hasan Sani Mohibur Rahman Md. Abdullah Al Achib Rakib Hossain B. Computer Science 2022-06-06T05:31:54Z 2022-06-06T05:31:54Z 2022 2022-01 Thesis ID 16201086 ID 16301156 ID 17101035 ID 17301165 http://hdl.handle.net/10361/16906 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. 30 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	CNN Deep learning VGG-19 Resnet-101 Inception v3 MRI image classification Detecting Alzheimer disease Cognitive learning theory (Deep learning) Alzheimer's disease. Neural networks (Computer science) Brain -- Imaging -- Mathematical models.
spellingShingle	CNN Deep learning VGG-19 Resnet-101 Inception v3 MRI image classification Detecting Alzheimer disease Cognitive learning theory (Deep learning) Alzheimer's disease. Neural networks (Computer science) Brain -- Imaging -- Mathematical models. Sani, Mehedi Hasan Rahman, Mohibur Achib, Md. Abdullah Al Hossain, Rakib An efficient deep learning approach for detecting Alzheimer’s disease using brain images
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
author2	Alam, Md. Ashraful
author_facet	Alam, Md. Ashraful Sani, Mehedi Hasan Rahman, Mohibur Achib, Md. Abdullah Al Hossain, Rakib
format	Thesis
author	Sani, Mehedi Hasan Rahman, Mohibur Achib, Md. Abdullah Al Hossain, Rakib
author_sort	Sani, Mehedi Hasan
title	An efficient deep learning approach for detecting Alzheimer’s disease using brain images
title_short	An efficient deep learning approach for detecting Alzheimer’s disease using brain images
title_full	An efficient deep learning approach for detecting Alzheimer’s disease using brain images
title_fullStr	An efficient deep learning approach for detecting Alzheimer’s disease using brain images
title_full_unstemmed	An efficient deep learning approach for detecting Alzheimer’s disease using brain images
title_sort	efficient deep learning approach for detecting alzheimer’s disease using brain images
publisher	Brac University
publishDate	2022
url	http://hdl.handle.net/10361/16906
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An efficient deep learning approach for detecting Alzheimer’s disease using brain images

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