CONVOLUTION NEURAL NETWORK BASED BRAIN TUMOR DETECTION USING EFFICIENT CLASSIFICATION TECHNIQUE

Abstract
An Excessive growth of unwanted cells in the brain is called brain tumor which is the most important barrier to prevent the rest of the brain from growing which can cause cancer. It was divided it into four types in total. The first type can easily remove these tumors surgically; the second type and the third type grow slowly and spread to nearby tissues, causing a small brain tumor. In this paper an efficient tumor detection method was proposed and these were performed well and identify the different levels of cancer with an efficient manner. In this proposed method focused on CNN image classification technique where the existing tumor images are available in the data base and the proposed method compare all the images and identify the size of the tumor, exact location and the level of the tumor. So the proposed method get high accurate results with short period of time.

Authors
T Kiruthiga
Vetri Vinayaha College of Engineering and Technology, India

Keywords
CNN Image Classification, Unwanted Cells, Brain Tumor, Surgical Tumors, Tumor Images
Published By :
ICTACT
Published In :
ICTACT Journal on Data Science and Machine Learning
( Volume: 3 , Issue: 2 )
Date of Publication :
March 2022

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.