Convolutional Neural Network For Binary Brain Tumor Classification Using MRI Scans

Abstract

Brain tumors are one of the most critical health conditions that require early and accurate diagnosis. This paper presents a Convolutional Neural Network (CNN)-based approach for binary classification of brain tumors using MRI images. The proposed system processes MRI scans through preprocessing and data augmentation techniques to improve model performance. The CNN model extracts important features and classifies images into tumor and non-tumor categories. The model achieves high accuracy with reduced computational complexity compared to existing multimodal approaches. This system helps in reducing manual effort and supports medical professionals in early diagnosis.