Medical Imaging Annotation for Diagnostic AI

Client: A healthcare AI startup developing FDA-pathway diagnostic imaging models Industry: Healthcare / Medical AI Services Used: Computer Vision, Expert Annotation, Regulatory-Grade Data

Challenge The startup was building deep learning models for early detection of a specific cancer type from CT and MRI scans. FDA submission required annotated training and validation datasets with radiologist-level labeling accuracy, full chain-of-custody documentation, and HIPAA-compliant handling of de-identified patient data. General-purpose annotation vendors could not provide medically qualified annotators or the regulatory rigor required, and in-house radiologist annotation was prohibitively expensive and slow.

Lifewood Solution Lifewood assembled a specialized annotation team including board-certified radiologists and medically trained annotators working under radiologist supervision. All work was performed in HIPAA-compliant environments with access controls, audit logging, and de-identification verification. A three-tier annotation protocol — primary annotator, radiologist review, consensus arbitration on disagreements — produced gold-standard labels. Every annotation decision was documented for FDA submission traceability.

Results

• 180,000 medical images annotated across CT and MRI modalities

• Radiologist-grade inter-annotator agreement of 0.94 Cohen's kappa

• Full FDA-submission-ready documentation delivered with the dataset

• 28% improvement in the client's model sensitivity vs. previous training set

• 100% HIPAA compliance maintained across 14 months of engagement

Representative Testimonial "Lifewood gave us the regulatory confidence we needed for FDA submission. Their documentation alone saved us months of compliance work." — Chief Medical Officer, client startup

Tags: Medical AI, Healthcare, Computer Vision, FDA Compliance, Regulatory-Grade Data