Brain Tumor MRI Image Segmentation using Deep Learning
Saumya Prasad, Muntzar Sayyed, Pratik Turkar, Ayush Tambe, Rashmi Jolhe
Brain tumour, MRI images, Resnet50 Architecture, CNN – Convolutional Neural Networks, Deep Learning
The proposed work aims to develop a segmentation model using Deep Learning Technique, which is a sub-part of Machine Learning. Using a CNN (Convolutional Neural Networks) model preferably Resnet50 Architecture, we aim to develop a model to detect tumours present in the patients’ brain MRI images. Initially, the model will classify the given dataset and segregate into images having tumour and no-tumour. Additionally, the model will highlight the tumour mask in the input image and will display the predicted mask along with the actual mask of the brain tumour. Our project mainly focuses on localization of the tumour and displaying its mask.
Article Details
Unique Paper ID: 159463

Publication Volume & Issue: Volume 9, Issue 12

Page(s): 26 - 33
Article Preview & Download

Share This Article

Conference Alert


AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2023

SWEC- Management


Last Date: 7th November 2023

Go To Issue

Call For Paper

Volume 10 Issue 1

Last Date for paper submitting for March Issue is 25 June 2023

About Us enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on

Social Media

Google Verified Reviews