Brain tumor detection with convolutional neural network

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Sonraí bibleagrafaíochta
Príomhchruthaitheoirí:	Galib, Abrar Tahmid, Taposh, Maruf Hasan, Nazim, Annas Mohd.
Rannpháirtithe:	Rahman, Rafeed
Formáid:	Tráchtas
Teanga:	English
Foilsithe / Cruthaithe:	Brac University 2024
Ábhair:	Convolutional neural networks (CNN) Neural network Machine learning Tumor detection MRI Inception V3 EfficientNetB0 Gray scaling Neural networks (Computer science) Artificial intelligence > Medical applications Deep learning (Machine learning)
Rochtain ar líne:	http://hdl.handle.net/10361/22827

id	10361-22827
record_format	dspace
spelling	10361-228272024-05-15T21:01:41Z Brain tumor detection with convolutional neural network Galib, Abrar Tahmid Taposh, Maruf Hasan Nazim, Annas Mohd. Rahman, Rafeed Hossain, Md.Iqbal Dofadar, Dibyo Fabian Department of Computer Science and Engineering, Brac University Convolutional neural networks (CNN) Neural network Machine learning Tumor detection MRI Inception V3 EfficientNetB0 Gray scaling Neural networks (Computer science) Artificial intelligence--Medical applications Deep learning (Machine learning) 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 52-54). The brain is the command center of our nervous system, which enables thoughts, memories, movements, and emotions. In other words, it is the most important organ in the human body. The human brain is very vulnerable to tumors, as merely growing old can be the cause of a tumor. Furthermore, the effects of a tumor can be fatal to a person because, as the tumor grows inside the brain, it can deform the structure of the brain and cause several diseases, the most fatal being cancer in the brain. Hence, to prevent such severe diseases, early detection of tumors is critical for a patient’s treatment. Moreover, modern technology has emerged to excellent heights, as MRI scans and CT scans can detect brain tumor regions. However, to accurately detect where the tumor is situated, a team of doctors is still needed to this day. Therefore, we have planned to use convolutional neural Networks to develop a faster and inexpensive method to detect tumors from MRI images in the early stages. Moreover, we plan to develop a system where our proposed CNN model will be able to detect tumors as well as identify three types of tumors, which are glioma, meningioma and pituitary tumors. Also, if there are no tumors, the system should be able to detect them too. To develop our proposed model, we have used data pre-processing techniques with a combination of gray scaling, One encoding, and CLAHE. Also, we have used a dataset of 6484 MRI images, segmenting them by testing and training. To compare and analyze our proposed model’s performance, we have tested and trained seven pre-trained models with the same dataset. The models are Vgg16, Vgg19, ResNet50, InceptionV3, DenseNet-121, EfficientNetB0, MobileNet and we received the following testing accuracy accordingly: 93.37%, 92.42%, 75.38%, 91.48%, 94.89%, 23.30% and 96.02%. However, the testing accuracy of our proposed model surpassed all the other pre-trained models, as it gained 98.11% accuracy in testing. In conclusion, we have aimed to build a CNN model that exceeds all the other CNN models in terms of overall performance, which is why we have integrated a sufficient amount of parameters to handle any unfavorable situations; however, the parameters are set in such a way that the overall system does not clutter and remains lightweight. Abrar Tahmid Galib Annas Mohd. Nazim Maruf Hasan Taposh B.Sc. in Computer Science 2024-05-15T04:17:45Z 2024-05-15T04:17:45Z ©2023 2023-09 Thesis ID: 19301246 ID: 19301223 ID: 19301082 http://hdl.handle.net/10361/22827 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. 66 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Convolutional neural networks (CNN) Neural network Machine learning Tumor detection MRI Inception V3 EfficientNetB0 Gray scaling Neural networks (Computer science) Artificial intelligence--Medical applications Deep learning (Machine learning)
spellingShingle	Convolutional neural networks (CNN) Neural network Machine learning Tumor detection MRI Inception V3 EfficientNetB0 Gray scaling Neural networks (Computer science) Artificial intelligence--Medical applications Deep learning (Machine learning) Galib, Abrar Tahmid Taposh, Maruf Hasan Nazim, Annas Mohd. Brain tumor detection with convolutional neural network
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.
author2	Rahman, Rafeed
author_facet	Rahman, Rafeed Galib, Abrar Tahmid Taposh, Maruf Hasan Nazim, Annas Mohd.
format	Thesis
author	Galib, Abrar Tahmid Taposh, Maruf Hasan Nazim, Annas Mohd.
author_sort	Galib, Abrar Tahmid
title	Brain tumor detection with convolutional neural network
title_short	Brain tumor detection with convolutional neural network
title_full	Brain tumor detection with convolutional neural network
title_fullStr	Brain tumor detection with convolutional neural network
title_full_unstemmed	Brain tumor detection with convolutional neural network
title_sort	brain tumor detection with convolutional neural network
publisher	Brac University
publishDate	2024
url	http://hdl.handle.net/10361/22827
work_keys_str_mv	AT galibabrartahmid braintumordetectionwithconvolutionalneuralnetwork AT taposhmarufhasan braintumordetectionwithconvolutionalneuralnetwork AT nazimannasmohd braintumordetectionwithconvolutionalneuralnetwork
_version_	1814307824352624640

Brain tumor detection with convolutional neural network

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