Published Paper Details:

The primary objective of SynapAI: AI-Powered Detection precise for Brain Tumors is to develop an advanced system for identifying brain tumors from MRI scans using a hybrid deep learning model integrating Convolutional Neural Networks (CNNs), Vision Transformers (ViT), and Capsule Networks (CapsNet). This system aims to assist medical professionals by providing an automated, accurate, and efficient diagnostic tool, enhancing precision while reducing manual effort. With brain tumors posing a significant health challenge, early detection is critical. SynapAI combines CNNs for local feature extraction, ViT for global context analysis, and CapsNet for preserving spatial hierarchies, achieving over 90% accuracy. Integrated with a Flask-based web interface using HTML and Tailwind CSS, the system processes uploaded MRI scans, applies preprocessing, and delivers real-time tumor classification. Historical MRI datasets ensure robust training and validation, positioning SynapAI as a valuable contribution to medical imaging technology.