Automatic brain tumor segmentation using U-ResUNet chain model approach

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

书目详细资料
Main Authors:	Alam, Mohd Tanjeem, Nawal, Nafisa, Nishi, Nusrat Jahan, Sahan, MD Samiul, Islam, Mohammad Tanjil
其他作者:	Akhond, Mosta jur Rahman
格式:	Thesis
语言:	English
出版:	Brac University 2022
主题:	Brain tumor Deep learning CNN LSTM Segmentation Res-Unet Unet Data train-test Comparison Result analysis Neural networks (Computer science) Cognitive learning theory (Deep learning) Machine learning
在线阅读:	http://hdl.handle.net/10361/16116

id	10361-16116
record_format	dspace
spelling	10361-161162022-02-06T21:06:41Z Automatic brain tumor segmentation using U-ResUNet chain model approach Alam, Mohd Tanjeem Nawal, Nafisa Nishi, Nusrat Jahan Sahan, MD Samiul Islam, Mohammad Tanjil Akhond, Mosta jur Rahman Department of Computer Science and Engineering, Brac University Brain tumor Deep learning CNN LSTM Segmentation Res-Unet Unet Data train-test Comparison Result analysis Neural networks (Computer science) Cognitive learning theory (Deep learning) Machine learning This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 37-41). Identifying brain tumors precisely within the early stage is still a challenging problem for the medical sector consistent with recent research. In a previous research approved by Cancer. Net Editorial Board, it was observed that this year, approximately twenty four thousand ve hundred thirty adults will be detected with initial stage cancer tumors of the brain and spinal cord in the United States. So, a developed technology is required to identify this tumor in an early stage to increase the survival rate from this disease. To overcome this problem, many Deep Learning models like CNN (Convolutional Neural Network), LSTM(Long-Short Term Memory) were proposed to detect tumor areas in the primary stage through segmentation and classi cation in previous research. In our proposed paper, we will attempt to use combination of Res-Unet and Unet model to perform segmentation on brain MRI images. So, basically, our target will be to take brain MRI images as input data and after that, we will try to t the combination of Unet and Res-Unet model on the dataset to perform segmentation to compare the result with other proposed models to get better result. Mohd Tanjeem Alam Nafi sa Nawal Nusrat Jahan Nishi MD Samiul Sahan Mohammad Tanjil Islam B. Computer Science 2022-02-06T09:11:24Z 2022-02-06T09:11:24Z 2021 2021-09 Thesis ID 17101223 ID 17201075 ID 17301070 ID 17101504 ID 15301110 http://hdl.handle.net/10361/16116 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. 41 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Brain tumor Deep learning CNN LSTM Segmentation Res-Unet Unet Data train-test Comparison Result analysis Neural networks (Computer science) Cognitive learning theory (Deep learning) Machine learning
spellingShingle	Brain tumor Deep learning CNN LSTM Segmentation Res-Unet Unet Data train-test Comparison Result analysis Neural networks (Computer science) Cognitive learning theory (Deep learning) Machine learning Alam, Mohd Tanjeem Nawal, Nafisa Nishi, Nusrat Jahan Sahan, MD Samiul Islam, Mohammad Tanjil Automatic brain tumor segmentation using U-ResUNet chain model approach
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
author2	Akhond, Mosta jur Rahman
author_facet	Akhond, Mosta jur Rahman Alam, Mohd Tanjeem Nawal, Nafisa Nishi, Nusrat Jahan Sahan, MD Samiul Islam, Mohammad Tanjil
format	Thesis
author	Alam, Mohd Tanjeem Nawal, Nafisa Nishi, Nusrat Jahan Sahan, MD Samiul Islam, Mohammad Tanjil
author_sort	Alam, Mohd Tanjeem
title	Automatic brain tumor segmentation using U-ResUNet chain model approach
title_short	Automatic brain tumor segmentation using U-ResUNet chain model approach
title_full	Automatic brain tumor segmentation using U-ResUNet chain model approach
title_fullStr	Automatic brain tumor segmentation using U-ResUNet chain model approach
title_full_unstemmed	Automatic brain tumor segmentation using U-ResUNet chain model approach
title_sort	automatic brain tumor segmentation using u-resunet chain model approach
publisher	Brac University
publishDate	2022
url	http://hdl.handle.net/10361/16116
work_keys_str_mv	AT alammohdtanjeem automaticbraintumorsegmentationusinguresunetchainmodelapproach AT nawalnafisa automaticbraintumorsegmentationusinguresunetchainmodelapproach AT nishinusratjahan automaticbraintumorsegmentationusinguresunetchainmodelapproach AT sahanmdsamiul automaticbraintumorsegmentationusinguresunetchainmodelapproach AT islammohammadtanjil automaticbraintumorsegmentationusinguresunetchainmodelapproach
_version_	1814309126930432000

Automatic brain tumor segmentation using U-ResUNet chain model approach

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