Deep learning based early Glaucoma detection

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

Detaylı Bibliyografya
Asıl Yazarlar:	Islam, Aabrar, Haque, Ayen Aziza, Tasnim, Najifa, Waliza, Simin
Diğer Yazarlar:	Karim, Dewan Ziaul
Materyal Türü:	Tez
Dil:	English
Baskı/Yayın Bilgisi:	Brac University 2024
Konular:	Convolutional neural network CNN Glaucoma diagnosis Disease detection Fundus image Neural networks (Computer science) Deep learning (Machine learning) Glaucoma > diagnosis
Online Erişim:	http://hdl.handle.net/10361/22872

id	10361-22872
record_format	dspace
spelling	10361-228722024-05-20T06:36:44Z Deep learning based early Glaucoma detection Islam, Aabrar Haque, Ayen Aziza Tasnim, Najifa Waliza, Simin Karim, Dewan Ziaul Department of Computer Science and Engineering, Brac University Convolutional neural network CNN Glaucoma diagnosis Disease detection Fundus image Neural networks (Computer science) Deep learning (Machine learning) Glaucoma--diagnosis This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024. Cataloged from PDF version of thesis. Includes bibliographical references (pages 53-54). Glaucoma is a severe eye condition that can lead to progressive vision impairment if left untreated. Diagnosis and monitoring of glaucoma at an initial stage is critical for effective treatment of the disease. However, the diagnosis is complex with bare eyes which requires multiple checkups and tests. Image processing is important for diagnosing glaucoma by providing valuable information about the intricate structure of the eye which helps improve the accuracy of diagnosis and allows for earlier detection of the disease. This portrays the requirement for further research in this field. We aim to explore various image-processing models used for image classification and develop an efficient model that can be used in the detection of glaucoma. In this paper, we have proposed a Custom CNN model with 22 layers based on deep learning for glaucoma diagnosis where it detects from the fundus images whether the person has glaucoma or not. The model has been trained using datasets containing 4000 fundus images each with 2 categories which are Glaucoma and Non-Glaucoma. The datasets have been used on the Custom CNN model and six other pre-trained models. Our proposed model has been able to successfully classify the images with an accuracy of 98.71% which was the highest among all the models despite having a lower number of parameters compared to the other models. Aabrar Islam Ayen Aziza Haque Najifa Tasnim Simin Waliza B.Sc in Computer Science 2024-05-19T08:56:57Z 2024-05-19T08:56:57Z ©2024 2024-01 Thesis ID: 20101361 ID: 20301487 ID: 20101406 ID: 20101401 http://hdl.handle.net/10361/22872 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. 67 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Convolutional neural network CNN Glaucoma diagnosis Disease detection Fundus image Neural networks (Computer science) Deep learning (Machine learning) Glaucoma--diagnosis
spellingShingle	Convolutional neural network CNN Glaucoma diagnosis Disease detection Fundus image Neural networks (Computer science) Deep learning (Machine learning) Glaucoma--diagnosis Islam, Aabrar Haque, Ayen Aziza Tasnim, Najifa Waliza, Simin Deep learning based early Glaucoma detection
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.
author2	Karim, Dewan Ziaul
author_facet	Karim, Dewan Ziaul Islam, Aabrar Haque, Ayen Aziza Tasnim, Najifa Waliza, Simin
format	Thesis
author	Islam, Aabrar Haque, Ayen Aziza Tasnim, Najifa Waliza, Simin
author_sort	Islam, Aabrar
title	Deep learning based early Glaucoma detection
title_short	Deep learning based early Glaucoma detection
title_full	Deep learning based early Glaucoma detection
title_fullStr	Deep learning based early Glaucoma detection
title_full_unstemmed	Deep learning based early Glaucoma detection
title_sort	deep learning based early glaucoma detection
publisher	Brac University
publishDate	2024
url	http://hdl.handle.net/10361/22872
work_keys_str_mv	AT islamaabrar deeplearningbasedearlyglaucomadetection AT haqueayenaziza deeplearningbasedearlyglaucomadetection AT tasnimnajifa deeplearningbasedearlyglaucomadetection AT walizasimin deeplearningbasedearlyglaucomadetection
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Deep learning based early Glaucoma detection

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