150K Medical Images Annotated Remotely in 16 Weeks with 99% Accuracy
- Industry: Healthcare Research & AI Development
- Challenges: Needed to annotate over 150,000 MRI brain scan images with detailed segmentation.
- Solution by: GetAnnotator by Macgence AI
Background
A prestigious university research lab was developing an AI-driven diagnostic system to detect early signs of neurological disorders from MRI and CT scan data. While they had expert researchers and advanced imaging technology, they lacked the large-scale, specialized annotation capability needed to prepare their datasets for AI training.
Challenge
The research team needed to annotate over 150,000 MRI brain scan images with detailed segmentation of regions associated with early-stage neurodegenerative diseases. Key obstacles included:
- Specialized Expertise: Required annotators with medical and radiology knowledge to ensure accuracy.
- Compliance: Adherence to HIPAA and academic data privacy standards.
- Scaling Resources: Need for rapid ramp-up to meet a six-month research grant deadline.
Their internal team could not balance high-level research tasks with the extensive manual labeling workload. Hiring a permanent team was not financially feasible for an academic project.
Solution
The lab partnered with GetAnnotator to deploy a specialized remote medical annotation team.
Key Actions Taken:
- Expert Team Allocation – 12 certified medical annotators with backgrounds in radiology and neurology assigned to the project.
- Customized Annotation Protocol – Workflow designed in collaboration with the research team to ensure precise identification of disease markers.
- Rigorous Quality Assurance – Multi-tier QA with a senior radiologist overseeing samples to maintain 99% accuracy.
- Secure Infrastructure – HIPAA-compliant cloud environment for secure data transfer and storage.
Outcome

| Metric | Before GetAnnotator | After GetAnnotator | Improvement |
|---|---|---|---|
| Dataset Size Prepared | 25,000 images in 26 weeks | 150,000 images in 16 weeks | 6× faster |
| Annotation Accuracy | 87% | 99% | +12% |
| Project Timeline Adherence | Delayed by 2 months | Completed 30% ahead | — |
| AI Model Early Disease Detection Accuracy | 68% | 83% | +22% |
In just 16 weeks, GetAnnotator delivered:
- 150,000+ MRI scans annotated with detailed segmentation.
- 99% labeling accuracy, validated by the lab’s lead radiologist.
- 30% faster project completion than initially projected.
As a result, the AI model trained on these annotations achieved a 22% improvement in early disease detection accuracy compared to previous datasets. The lab met its research grant deadline, published findings in a peer-reviewed journal, and secured additional funding to expand the project to multi-modal imaging.
Impact
The collaboration enabled the research lab to:
- Accelerate research timelines by removing data preparation bottlenecks.
- Improve dataset quality, leading to more accurate AI predictions.
- Scale resources cost-effectively, avoiding the expense of permanent hires.
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