X-ray Annotation Services for Medical Imaging AI (Chest, Bone, Dental, Spine)

X-ray annotation is the labeling of radiographic images to train AI models for detection, classification, segmentation, or measurement. Accurate guidelines and consistent QA are essential to reduce label noise and improve model generalization across devices and populations.

We support regions of interest, bounding boxes, pixel-level segmentation, keypoint/landmark labeling, and structured pathology tags. Labels can be tailored to your ontology and clinical objectives, including multi-label findings and severity grading where appropriate.

Common use cases include pneumonia and lesion detection, fracture identification, dental and maxillofacial analysis, spine measurements, and triage workflows. We support dataset preparation for model training, validation, and testing.

Quality controls include label consistency checks, sampling audits, review loops, and targeted rework for hard cases. Sensitive datasets can be processed under GDPR-aligned workflows with EU-only annotation options where required.