teeth labeling Computer Vision Project

Description: This project focuses on automating the detection and labeling of various types of teeth in dental images. The primary objective is to assist dental professionals in analyzing and diagnosing dental conditions by accurately identifying different types of teeth. The project utilizes computer vision techniques to detect and classify the following types of teeth:

1. Central Incisors: Identify and locate the central incisors in the dental images.
2. Lateral Incisors: Detect and label the lateral incisors within the dental images.
3. Canines: Locate and classify the canines present in the dental images.
4. Premolars: Detect and categorize premolar teeth visible in the dental images.
5. Molars: Identify and label the molars present in the dental images.

By accurately labeling these types of teeth, our model aims to provide dental professionals with valuable insights and assist in diagnosing dental conditions efficiently.

Dataset: The dataset used for training and evaluation consists of annotated dental images containing various types of teeth, including central incisors, lateral incisors, canines, premolars, and molars. Each image is annotated with bounding boxes or segmentation masks to indicate the location and extent of individual teeth within the image.

Applications: The trained model has applications in various dental tasks, including:

• Dental diagnosis and treatment planning
• Automated tooth counting and segmentation
• Orthodontic treatment planning
• Dental research and analysis

Future Enhancements: Future enhancements to this project may include:

• Fine-tuning the model on larger and more diverse datasets
• Integrating the model into dental software platforms for real-time analysis and decision support