Predicting the Existence of Brain Tumor in Mri Images by Applying FCNN

Authors

  • Sylvester Ranjith F1 , Parveen Sultana H2

DOI:

https://doi.org/10.37506/mlu.v20i3.1426

Keywords:

Image processing, Machine learning, Deep Learning, Neural Networks, Fully Connected Convolutional Neural Networks, Image Segmentation, Tumor Detection, HGG, LGG, Convolutional Layer.

Abstract

Brain tumors are major causes of death in today’s world and methods of detecting them prematurely require

vast improvement. The objective of this project is to detect the tumors early from MR image scans by

utilizing deep convolutional networks to locate the tumor.The tumor is divided at first in the main stage and

the generated bounding box is utilized for the center of the tumor in second step. This is trailed by division

based on the bounding box of the tumor center division result. Examinations are performed with the BraTS

2017 validation set. This is a numerous division issue.

Author Biography

Sylvester Ranjith F1 , Parveen Sultana H2

1Student, 2Associate Professor, School of Computer Science and Engineering, Vellore Institute of Technology,

632014 Vellore, India

Published

2020-07-24

How to Cite

Sylvester Ranjith F1 , Parveen Sultana H2. (2020). Predicting the Existence of Brain Tumor in Mri Images by Applying FCNN. Medico Legal Update, 20(3), 375-380. https://doi.org/10.37506/mlu.v20i3.1426