AI-Powered Web Application for Oral Cancer Detection and Treatment Recommendation Using CNN on MRI, CT, and PET Scans

Oral cancer is a serious disease that requires early detection to improve patient survival. Traditional diagnostic methods such as visual screening and biopsy are time-consuming and uncomfortable for patients. This project presents an automated oral cancer detection system using medical images and a Binary Convolutional Neural Network (Binary CNN). The system analyzes oral region scan images and classifies them into two categories: cancerous and non-cancerous. Image preprocessing techniques improve quality before feature extraction. The Binary CNN automatically learns tumor-related patterns and performs accurate classification. The system focuses only on oral cancer detection and does not include multi-disease analysis. This approach reduces manual effort, supports faster diagnosis, and assists medical professionals in early screening using a simple and reliable computer-based detection system.