This project leverages deep learning techniques to detect and predict various dental diseases from panoramic dental X-ray images (OPG - Orthopantomogram). It uses the YOLOv8 object detection model for localizing and identifying diseased regions, enabling automated screening and assistance for dental professionals.

Python viewer for .BPT tomography files with MPR, frontal MIP, and curved panoramic reconstruction

End-to-end implementation of "CephLD-CCA: Cephalometric Landmark Detection with Cartesian Coordinate Channel Attention", released for reproducibility and reusability

Sistema de detección de 14 anomalías dentales con IA usando YOLOv8 - Herramienta web interactiva para asistir a odontólogos en el análisis de radiografías panorámicas. Incluye aplicación web con Streamlit, visualización interactiva y generación de reportes PDF.

🦷 Dental CAD web application for designing crowns, inlays/onlays and bridges from intraoral scans (STL/PLY) — React + Three.js viewer, Float64 TypeScript geometry kernel with manifold-3d WASM booleans, Fastify backend with independent export re-validation.

High-end intraoral scan classification using Deep Learning. A professional clinical tool for automated dental diagnostics with a premium UI/UX.

UNet-EfficientNet pipeline for automated crown–apex detection and dental working length estimation from periapical X-rays.

Automated system for tooth decay detection from intraoral images using CNN.

PyTorch Lightning implementation of a 5-class dental pathology segmentation system using a U-Net with a pre-trained ResNet34 backbone, joint Dice-CE loss, and power-law smoothed class weighting.

Biomedical image analysis of dental radiographs using machine learning, deep learning, and computer vision techniques developed during a research internship at IISc Bangalore.

Windows UVC intraoral camera preview and photo capture utility

OHIF-based dental CBCT viewer with MPR ,CPR and panoramic reconstruction