An Efficient deep learning approach to detect Brain Tumor using MRI images

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021.

Dettagli Bibliografici
Autori principali:	Islam, Annur Tasnim, Apu, Sakib Mashra, Sarker, Sudipta, Hasan, Inzamam M., Shuvo, Syeed Alam
Altri autori:	Alam, Md. Ashraful
Natura:	Tesi
Lingua:	English
Pubblicazione:	Brac University 2022
Soggetti:	Brain Tumor MRI Deep Neural Network VGG ResNet Efficient- Net Inception Ensemble EBTDM Neural networks (Computer science) Image processing > Digital techniques
Accesso online:	http://hdl.handle.net/10361/17179

id	10361-17179
record_format	dspace
spelling	10361-171792022-09-08T21:01:38Z An Efficient deep learning approach to detect Brain Tumor using MRI images Islam, Annur Tasnim Apu, Sakib Mashra Sarker, Sudipta Hasan, Inzamam M. Shuvo, Syeed Alam Alam, Md. Ashraful Rodoshi, Ahanaf Hassan Department of Computer Science and Engineering, Brac University Brain Tumor MRI Deep Neural Network VGG ResNet Efficient- Net Inception Ensemble EBTDM Neural networks (Computer science) Image processing -- Digital techniques This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 33-35). A brain tumor is the development of mutated cells in the human brain. Many di er- ent types of brain tumors exist nowadays. According to researchers and physicians, some brain tumors are non-cancerous while some are life-threatening. In most cases, the cancer is detected at the last stage and it is di cult to recover. This increases the mortality rate. If this could be detected in the initial stages, then a lot more lives could be saved. Nowadays, brain tumors are being detected through auto- mated processes using arti cial intelligence algorithms and brain image data. In this research, we propose an e cient approach to detect brain tumors using Mag- netic Resonance Imaging (MRI) data and a deep neural network. The proposed system comprises several steps - preprocessing and classi cation of brain MRI im- ages. Furthermore, we analyzed the performances of di erent deep neural network architectures and optimized them with an e cient one. The proposed model en- ables classifying brain tumors e ectively with higher accuracy. To commence, we collected data and classi ed it using the ResNetl0l, ResNet50, InceptionV3, VGG19, and VGG19 architectures. As a consequence of our analysis, we obtained an accu- racy rate of 96.72% for VGG16, 96.17% for ResNet50, and 95.55% for InceptionV3. Then, using these three top classi ers, we constructed an ensemble model and ob- tained an overall accuracy rate of 98.60% using EBTDM (Explainable Brain Tumor Detection Model). Annur Tasnim Islam Sakib Mashra Apu Sudipta Sarker Inzamam M. Hasan Syeed Alam Shuvo B. Computer Science 2022-09-08T05:03:34Z 2022-09-08T05:03:34Z 2021 2021-10 Thesis ID 18101021 ID 21141078 ID 18101631 ID 21241084 ID 21141080 http://hdl.handle.net/10361/17179 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. 35 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Brain Tumor MRI Deep Neural Network VGG ResNet Efficient- Net Inception Ensemble EBTDM Neural networks (Computer science) Image processing -- Digital techniques
spellingShingle	Brain Tumor MRI Deep Neural Network VGG ResNet Efficient- Net Inception Ensemble EBTDM Neural networks (Computer science) Image processing -- Digital techniques Islam, Annur Tasnim Apu, Sakib Mashra Sarker, Sudipta Hasan, Inzamam M. Shuvo, Syeed Alam An Efficient deep learning approach to detect Brain Tumor using MRI images
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021.
author2	Alam, Md. Ashraful
author_facet	Alam, Md. Ashraful Islam, Annur Tasnim Apu, Sakib Mashra Sarker, Sudipta Hasan, Inzamam M. Shuvo, Syeed Alam
format	Thesis
author	Islam, Annur Tasnim Apu, Sakib Mashra Sarker, Sudipta Hasan, Inzamam M. Shuvo, Syeed Alam
author_sort	Islam, Annur Tasnim
title	An Efficient deep learning approach to detect Brain Tumor using MRI images
title_short	An Efficient deep learning approach to detect Brain Tumor using MRI images
title_full	An Efficient deep learning approach to detect Brain Tumor using MRI images
title_fullStr	An Efficient deep learning approach to detect Brain Tumor using MRI images
title_full_unstemmed	An Efficient deep learning approach to detect Brain Tumor using MRI images
title_sort	efficient deep learning approach to detect brain tumor using mri images
publisher	Brac University
publishDate	2022
url	http://hdl.handle.net/10361/17179
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An Efficient deep learning approach to detect Brain Tumor using MRI images

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