Detecting brain tumor using deep neural networks from MRI images

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.

Description

Cataloged from PDF version of thesis.
Includes bibliographical references (page 38-39).
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Keywords

CNN, VGG16, ResNet50, Brain Tumor

Citation

Endorsement

Review

Supplemented By

Referenced By