High-Quality Image Annotation for AI-Powered Diagnostics
The Client
The Client, a healthcare technology company, developed a mobile app that leverages AI to assist patients and clinicians in monitoring wound health. Their AI-powered model required precise annotations to ensure clinician-level accuracy in wound measurement and diagnostics.
The Challenge
To deliver highly accurate wound assessments, the Client needed large-scale, high-quality annotations for their computer vision (CV) model. In-house labeling proved too expensive to scale, while outsourced providers struggled to meet the required precision. The Client needed a reliable partner capable of upskilling annotators to accurately label wound tissue types and boundaries.
The Solution
Hugo implemented a structured annotation workflow to ensure accuracy while scaling.
Expert Team Formation: Hugo selected annotators with a healthcare background, providing specialized training in wound diagnostics with input from the Client's clinical team. A 30% dataset subset was labeled and validated before full-scale implementation to ensure quality.
Integrated Feedback Loops: The team established real-time communication channels via Slack, email, and phone, allowing for immediate discussions on edge cases. This iterative approach helped refine labeling instructions, reduce annotation time per task, and manage increasing task complexity effectively.
Multi-Layered Quality Assurance: Hugo established a robust QA framework, incorporating automated checks and a dedicated team that regularly collaborated with the Client for sampling. Weekly feedback sessions facilitated continuous improvements in both annotation accuracy and process efficiency.
The Results
High-Precision Annotation – achieved 98.5% accuracy, enhancing AI diagnostic reliability.
Scalable Operations – Labeled 500,000+ medical images in six months.
Faster AI Training – Reduced annotation time by 40%, accelerating dataset processing.
“Hugo stood out from the other vendors we'd worked with previously. Their team maintained consistent communication and stayed engaged from start to finish, creating a significantly better experience." —Carter A., Senior Machine Learning Researcher
Strategic Impact
Through expert training, continuous feedback, and rigorous quality measures, Hugo delivered scalable, high-precision annotations that elevated the Client's AI performance and patient monitoring capabilities.
