Indonesian Journal of Electronics and Instrumentation Systems
Vol 8, No 2 (2018): October

Brain Tumor Classification Using Gray Level Co-occurrence Matrix and Convolutional Neural Network

Wijang Widhiarso (STMIK Global Informatika MDP Palembang)
Yohannes Yohannes (STMIK Global Informtika MDP PAlembang)
Cendy Prakarsah (STMIK Global Informatika MDP Palembang)



Article Info

Publish Date
31 Oct 2018

Abstract

Image are objects that have many information. Gray Level Co-occurrence Matrix is one of many ways to extract information from image objects. Wherein, the extracted informations can be processed again using different methods, Gray Level Co-occurrence Matrix is use for clarifying brain tumor using Convolutional Neural Network. The scope in this research is to process the extracted information from Gray Level Co-occurrence Matrix to Convolutional Neural Network where it will processed as Deep Learning to measure the accuracy using four data combination from TI1, in the form of brain tumor data Meningioma, Glioma and Pituitary Tumor. Based on the implementation of this research, the classification result of Convolutional Neural Network shows that the contrast feature from Gray Level Co-occurrence Matrix can increase the accuracy level up to twenty percent than the other features. This extraction feature is also accelerate the classification process using Convolutional Neural Network.

Copyrights © 2018






Journal Info

Abbrev

ijeis

Publisher

Subject

Electrical & Electronics Engineering

Description

IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), a two times annually provides a forum for the full range of scholarly study. IJEIS scope encompasses all aspects of Electronics, Instrumentation and Control. IJEIS is covering all aspects of Electronics and Instrumentation ...