Segmentation And Classification Of Brain Tumor Using CNN Algorithm

Segmentation and classification of brain tumors using Convolutional Neural Networks (CNN) is a critical advancement in medical imaging, offering precise and automated analysis of brain scans. This study presents a CNN-based framework designed to accurately segment and classify brain tumors from MRI images. The proposed method leverages the deep learning capabilities of CNNs to discern tumor boundaries and classify tumor types, ensuring high accuracy and efficiency. Through extensive training on annotated datasets, the CNN model learns to identify complex patterns and features unique to various tumor types. The results demonstrate significant improvements in both segmentation and classification performance, underscoring the potential of CNNs in enhancing diagnostic processes and aiding in clinical decision-making.