Article

No Article found
CROSSREF PEER REVIEWED GOOGLE SCHOLAR PLAGIARISM CHECK
ISSN License

A Review on Predictive Based Brain Tumor Detection Techniques

Author: Dr. S. S. Shirgan, Kanchan Waghmare Department of Electronics and Telecommunication, N B Navale College of Engineering,Solapur.

Published On: 2022-09-17

Abstract

The brain tumors, are the most common and aggressive disease, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of patients. Generally, various image techniques such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and ultrasound image are used to evaluate the tumor in a brain, lung, liver, breast, prostate…etc. Especially, in this work MRI images are used to diagnose tumor in the brain. However the huge amount of data generated by MRI scan thwarts manual classification of tumor vs non-tumor in a particular time. But it having some limitation (i.e) accurate quantitative measurements is provided for limited number of images. Hence trusted and automatic classification scheme are essential to prevent the death rate of human. The automatic brain tumor classification is very challenging task in large spatial and structural variability of surrounding region of brain tumor. In this work, automatic brain tumor detection is proposed by using Convolutional Neural Networks (CNN) classification. If tumor is detected system classified the tumor and conveys patient the stage of tumor he is probably suffering.

Keywords- Convolution Neural Network (CNN), MRI, tumors.

Keywords
- Convolution Neural Network (CNN) MRI tumors.
Article Information
Volume

5

Year

2022

Review Rounds

1

Article Type

Research Article

Indexed In
Publish your academic thesis as a book with ISBN Contact – connectirj@gmail.com
Get In Touch

2/11, SASTRI NAGAR, KOYEMBEDU, CHENNAI-600107

9488577176

editor@irjweb.com, connectirj@gmail.com

Follow Us

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

Copyrights © IRJEdT. All Rights Reserved.

Visiters Count :