Medical Annotation Services for Imaging, Video, Clinical NLP, and Biosignals

Medical annotation is the process of labeling healthcare data so models can detect findings, segment anatomy, extract entities, or classify clinical events. It requires precise guidelines, domain-aware review, and consistent QA to reduce noise in training and evaluation datasets.

We annotate radiology images (MRI, CT, X-ray, ultrasound), pathology and microscopy, procedural video, clinical text and EHR-derived documents, and biosignals (ECG, EEG, EMG). Label types include segmentation, bounding boxes, landmarks, classification, and structured clinical NLP labels.

Use cases include detection and triage, organ and lesion segmentation, pathology region labeling, clinical entity extraction, cohort building, and signal event detection. We adapt ontologies and guidelines to your clinical objectives and evaluation criteria.

Quality controls include multi-stage review, sampling audits, inter-annotator consistency checks, and targeted adjudication in ambiguous cases. Sensitive datasets can be handled under GDPR-aligned workflows with EU-only annotation options where required.