Large-Scale Dental X-ray Annotation for AI Diagnostics: 25,000+ Images

Dental Image Annotation Polygon & Keypoint Segmentation, AI-Assisted Labeling, Medical Data Quality Control, HIPAA-Compliant Data Processing

The objective of the project was to create a high-quality, large-scale dental X-ray dataset suitable for training and validating AI models used in automated diagnostics.

The dataset included both panoramic and intraoral dental X-rays, provided in DICOM and PNG formats, covering a wide range of patient anatomies, dental conditions, and imaging variations. Precision, consistency, and anatomical correctness were critical to ensure reliable model performance in real clinical settings.

Dental X-ray interpretation requires fine-grained annotation and strong anatomical understanding. The client faced several challenges:

• High variability in dental anatomy and imaging quality across patients

• Need for detailed, tooth-level segmentation aligned with clinical numbering standards (1–32)

• Requirement for fast turnaround without compromising annotation accuracy

• Strict HIPAA compliance and data security obligations

The client needed a scalable annotation partner capable of delivering clinical-grade dental datasets within tight timelines.

Mindy Support was selected for its deep experience in medical and dental image annotation and its ability to combine AI-assisted workflows with expert human validation.

Key differentiators included:

• Annotation teams trained in dental anatomy and radiographic interpretation

• Proven workflows for high-volume medical image annotation

• Secure, HIPAA-compliant annotation environments

• Strong quality assurance processes tailored to healthcare AI use cases

Mindy Support designed and executed a hybrid AI + human annotation pipeline optimized for dental imaging.

Key Workstreams

• Comprehensive annotation of dental structures, including: teeth (1 – 32), roots and crowns, fillings, implants, and restorations, dental caries and cavities

• High-precision polygon and keypoint segmentation for fine-grained model training

• AI-assisted pre-labeling to accelerate throughput, followed by expert human review

• Multi-level quality control to ensure clinical consistency and labeling accuracy

• End-to-end delivery within a HIPAA-compliant operational framework

• 25,000+ annotated dental X-rays delivered in 6 weeks

• 31% improvement in disease detection accuracy

• 27% increase in segmentation IoU across benchmark tests

• Enabled the launch of a next-generation AI dental diagnostic system, now progressing through regulatory testing