Segmentation and Classification of Human Brain Using Tumor Cut and Convolution Neural Network

  • S. Ananthanayaki, Dr. A. Annadhason

Abstract

A brain tumor detecting in MRI image will spend more time and the process is hard to classify it and also in the brain tumor image segmentation it faces too many overlapping regions during the segmentation. In this paper we were introduced the tumor cut segmentation to separate the tumor tissue into necrotic and enhance the part to analyses the tumor. We propose CNN (Convolutional Neural Network) to detect the similarities of the segmented image. The CNN scheme help to classify the type of cancer that caused by the tumor. The main objective if this paper is, the brain tumor will being varied in the size, a shape and the location of a tumor in the brain. So the tumor cut assists to analyse the tumor by splitting its tissue region and CNN will classify the brain tumor to the respected cancer type.

Published
2021-11-23
How to Cite
S. Ananthanayaki, Dr. A. Annadhason. (2021). Segmentation and Classification of Human Brain Using Tumor Cut and Convolution Neural Network. Design Engineering, 14928 - 14936. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/6628
Section
Articles