An Intelligent System for Classification of Brain Tumours With GLCM and Back Propagation Neural Network

Bhukya Jabber, K. Rajesh, D. Haritha, CMAK Zeelan Basha, Syed Nazia Parveen

20202020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA)17 citationsDOI

Abstract

Currently, technology has shown a lot of advancement in the field of medicine. Modalities available for capturing the brain images are Magnetic Resonance Imaging (MRIs), Positron Emission Tomography (PET) scan, and Computed Tomography (CT) scan. Among these MR is the most significantly used tool for judgment related to the anatomy of the brain. It is very essential for the classification of tumors in early-stage which supports avoiding the deaths due to brain tumors. Computerized classification of the tumor using MRI is proposed where features are extracted using the Gray Level Co-occurrence Matrices (GLCM) and classification using the BPNN. An accuracy of 94% is achieved with the proposed methodology.

Topics & Concepts

Positron emission tomographyMagnetic resonance imagingArtificial intelligenceComputer scienceArtificial neural networkNeuroimagingComputed tomographyBrain tumorModalitiesRadiologyPattern recognition (psychology)MedicinePathologySocial scienceSociologyPsychiatryBrain Tumor Detection and ClassificationNeural Networks and ApplicationsMedical Image Segmentation Techniques