Annotated complex dental X-ray medical imaging datasets used to train AI models for healthcare applications.

The project involved precise labeling of anatomical structures including teeth boundaries, roots, and surrounding regions using polygon and keypoint annotation techniques.

The objective was to generate high-quality training datasets that allow machine learning systems to accurately detect dental structures and support medical imaging analysis.

Responsibilities included: • Image segmentation and polygon annotation • Keypoint labeling for anatomical structures • Dataset preparation for machine learning models • Annotation quality control and validation

This work contributes to the development of AI systems used in medical diagnostics and healthcare imaging analysis.