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    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
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    Detecting brain tumor using deep neural networks from MRI images

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    20141034, 16201013, 17101064, 17101279, 17101135_CSE.pdf (2.341Mb)
    Date
    2021-06
    Publisher
    Brac University
    Author
    Imamuzzaman, A.S.M.
    Sakline, Redwan Islam
    Junaed, Sayed Rafi
    Hossain, Mohammad Iqbal
    Das, Dipto
    Metadata
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    URI
    http://hdl.handle.net/10361/15203
    Abstract
    A brain tumor is a collection of abnormal cells growth in brain. It is a neurological disease which causes great damage and affects other healthy cells of brain. It can be cancerous or non-cancerous. Nowadays, people are more concern about their health issues. So, in this thesis paper we will design and implement an efficient machine learning approach to detect brain tumor from image data. Moreover, the proposed model approaches VGG16 and ResNet50 architectural model of Convolutional Neu ral Network (CNN). Through this model a neurosurgeon can easily detect the brain tumor of a patient with more efficiency. Our proposed model uses MRI images, and we also make a comparison between the two architectures of CNN.
    Keywords
    CNN; VGG16; ResNet50; Brain Tumor
     
    LC Subject Headings
    Brain Tumor
     
    Description
    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 (page 38-39).
    Department
    Department of Computer Science and Engineering, Brac University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

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