Detection and classification of brain tumor using Artificial Neural Network from EEG Images

Abstract

Brain tumor is an abnormal intracranial growth caused by cells reproducing themselves in an uncontrolled manner. Curing cancer has been a major goal of medical researchers for decades. The early detection of cancer can be helpful in curing the disease completely. In this paper we propose an ANN base approach to identify brain tumor from electroencephalogram (EEG) signals. It mainly consists of three stages; they are pre-processing, feature extraction and classification. The preprocessing involves resizing so that the further processing is easier. Feature Extraction involves extracting the features. The classification stage involves Artificial Neural network. Raw EEG signals are valuable in brain tumor diagnosis. On this basis, a brain tumor identification system is developed to analyze those features to judge whether brain tumor is present or not.

Authors and Affiliations

Shashi Kiran. S| Assistant Professor, JNN College of Engineering, Shimoga, Karnataka, India E-mail: shashisurya81@gmail.com, Liyakathunisa| Assistant Professor, Sri Jayachamarajendra College of Engineering, Mysore, Karnataka, India E-mail: dr.liyakath@yahoo.com

Keywords

Related Articles

A Secure and authorized Duplication model in Cloud Using multi-layered cryptosystem based

the present a scheme that permits a more fine-grained trade-off. The intuition is that outsourced data may require different levels of the protection, depending on how to popular it is: content shared by many users,...

Dispensing Iptv Amenities Through Simulation By Enhancing Cloud Possessions

Prenent we are having virtual technologies these are failure on quality of services.The development of IPTV service delivery through cloud services is of temporary interest in many applications such as failure findi...

A Reconfigurable Less Power Asynchronous FPGA Design with Power Gating and Level encoding dual rail technique

The implementation of a low power logic based asynchronous circuit with the help of power gated logic. In asynchronous power gated logic (APL) circuit, each pipeline stage was incorporated with efficient charge recov...

Accelerometer Based Vehicle Monitoring And Tracking System Using ARM Processor And GPS

This paper mainly deals with concept of Vehicle tracking, Monitoring and providing security by theft. This system is based on ARM7, GSM and GPS is proposed. GSM technology is used to send information about the vehicl...

We propose another revocable IBE plot with a cloud revocation authority (CRA) to unravel the two inadequacies, to be specific, the execution is essentially enhanced and the CRA holds just a framework mystery for ever...

Download PDF file
  • EP ID EP16241
  • DOI -
  • Views 387
  • Downloads 16

How To Cite

Shashi Kiran. S, Liyakathunisa (2013). Detection and classification of brain tumor using Artificial Neural Network from EEG Images. International Journal of Science Engineering and Advance Technology, 1(7), 211-218. https://europub.co.uk/articles/-A-16241