Dental Cavity Detection Dataset

Dataset Overview

The Dental Cavity Detection Dataset is a comprehensive collection of 418 annotated dental images, meticulously labeled for cavities using the YOLOv5 Oriented Object Detection format. This dataset is tailored to support advanced research and development in AI-driven dental diagnostics and is compatible with modern object detection frameworks.

Key Features

• Detailed Annotations: Each dental image is precisely labeled to highlight cavity locations, ensuring high-quality data for training and evaluation.
• YOLOv5 Compatibility: Optimized for seamless integration with popular object detection frameworks, accelerating AI model development.
• Specialized Focus: Designed specifically for cavity detection in dental X-rays, making it ideal for targeted research and applications.

Applications

• Automated Dental Diagnostics: Train machine learning models to detect and localize cavities with high accuracy.
• Computer Vision in Healthcare: Advance medical imaging technologies focused on dental health.
• AI-Assisted Dentistry: Develop tools that assist dentists in faster, more reliable cavity detection and diagnosis.

This dataset is sourced from Kaggle.