Automated Brain Tumour Classification using Deep Learning Technique

¹ Department of CSBS, GRIET, Hyderabad, Telangana State, India
² Uttaranchal Institute of Technology, Uttaranchal University, Dehradun, 248007, India
³ KG Reddy College of Engineering & Technology, Hyderabad, India.

^* Corresponding author: mamidi.kirankumar09@gmail.com

Abstract

Brain Tumour is a severe condition caused due to abnormal growth of cells in the brain. Brain Tumour is broadly classified into two categories namely Malignant (Cancerous) and Benign (Non-Cancerous). As tumour grows, the pressure within the skull can increase which can damage the brain and be life-threatening. Early detection and classification of the brain tumours is important as it helps to select the most appropriate treatment for saving the patient’s life. Usually, Brain Tumour Detection can be done manually by the doctors or use machine learning models in case of MRI images of the brain. In literature, it is identified that deep learning techniques such as CNN, DCNN and RNN show good results in image processing applications. This paper aims to detect and classify the Brain Tumours effectively using CNN deep learning techniques. The dataset is collected from Kaggle. The proposed method achieved an accuracy of 93.5% and 98.4% with CNN and Resnet50 respectively.