Classification of retinal diseases from OCT images using deep learning models

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

Podrobná bibliografie
Hlavní autoři:	Mokarrom, Md Saif, Shuvo, Md Anonto, Oyon, Nazmul Hasan, Munaja, Rifha Hossain, Roy, Soumik
Další autoři:	Alam, Md. Ashraful
Médium:	Diplomová práce
Jazyk:	English
Vydáno:	Brac University 2024
Témata:	GradCAM Convolutional neural network Retina classification Machine learning > Medical applications Diagnostic imaging > Data processing Neural networks (Computer science) Deep learning (Machine learning)
On-line přístup:	http://hdl.handle.net/10361/22885

id	10361-22885
record_format	dspace
spelling	10361-228852024-05-20T21:00:33Z Classification of retinal diseases from OCT images using deep learning models Mokarrom, Md Saif Shuvo, Md Anonto Oyon, Nazmul Hasan Munaja, Rifha Hossain Roy, Soumik Alam, Md. Ashraful Shakil, Arif Department of Computer Science and Engineering, Brac University GradCAM Convolutional neural network Retina classification Machine learning--Medical applications Diagnostic imaging--Data processing Neural networks (Computer science) Deep learning (Machine learning) 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 61-63). Retina is an important part of our vision, but it can easily get affected and create various vision problems like vision loss and others. According to the statistics provided by The World Health Organization, it is estimated that globally at least 2.2 billion people suffer from various retinal disorders. It’s important to accurately classify retinal diseases since early detection can help in taking steps for treatment. In this paper, we have classified different types of retinal diseases which are based on OCT images. OCT images were used because they produce a lot of fine-grained retinal images that are useful for diagnosing and monitoring changes to the retina and optic nerve over time. For the classification, we have used Deep learning Models such as CNN models for predicting the accuracy. Moreover, we have proposed a new model for the classification. Our custom model gives an accuracy of 95.05% which is better compared to other pre-trained models. Both DME and DRUSEN class obtained maximum precision that is 97% and Normal class obtained maximum recall which is 98%. Furthermore, we have used Explainable AI (XAI) Techniques with Grad-CAM for better analysis and created a web application for live visualization of result. Md Saif Mokarrom Md Anonto Shuvo Nazmul Hasan Oyon Rifha Hossain Munaja Soumik Roy B.Sc in Computer Science 2024-05-20T06:28:20Z 2024-05-20T06:28:20Z ©2024 2024-01 Thesis ID: 20301121 ID: 23141036 ID: 20101528 ID: 20301466 ID: 20101573 http://hdl.handle.net/10361/22885 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. 70 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	GradCAM Convolutional neural network Retina classification Machine learning--Medical applications Diagnostic imaging--Data processing Neural networks (Computer science) Deep learning (Machine learning)
spellingShingle	GradCAM Convolutional neural network Retina classification Machine learning--Medical applications Diagnostic imaging--Data processing Neural networks (Computer science) Deep learning (Machine learning) Mokarrom, Md Saif Shuvo, Md Anonto Oyon, Nazmul Hasan Munaja, Rifha Hossain Roy, Soumik Classification of retinal diseases from OCT images using deep learning models
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.
author2	Alam, Md. Ashraful
author_facet	Alam, Md. Ashraful Mokarrom, Md Saif Shuvo, Md Anonto Oyon, Nazmul Hasan Munaja, Rifha Hossain Roy, Soumik
format	Thesis
author	Mokarrom, Md Saif Shuvo, Md Anonto Oyon, Nazmul Hasan Munaja, Rifha Hossain Roy, Soumik
author_sort	Mokarrom, Md Saif
title	Classification of retinal diseases from OCT images using deep learning models
title_short	Classification of retinal diseases from OCT images using deep learning models
title_full	Classification of retinal diseases from OCT images using deep learning models
title_fullStr	Classification of retinal diseases from OCT images using deep learning models
title_full_unstemmed	Classification of retinal diseases from OCT images using deep learning models
title_sort	classification of retinal diseases from oct images using deep learning models
publisher	Brac University
publishDate	2024
url	http://hdl.handle.net/10361/22885
work_keys_str_mv	AT mokarrommdsaif classificationofretinaldiseasesfromoctimagesusingdeeplearningmodels AT shuvomdanonto classificationofretinaldiseasesfromoctimagesusingdeeplearningmodels AT oyonnazmulhasan classificationofretinaldiseasesfromoctimagesusingdeeplearningmodels AT munajarifhahossain classificationofretinaldiseasesfromoctimagesusingdeeplearningmodels AT roysoumik classificationofretinaldiseasesfromoctimagesusingdeeplearningmodels
_version_	1814307017922183168

Classification of retinal diseases from OCT images using deep learning models

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