Tool Adaptation & Technical Learning
MD.ai's interface and 3D segmentation tools required hands-on familiarisation. The team built SOPs and leveraged client-provided walkthrough videos and reference documents to accelerate onboarding.
Casestudy
Data Annotation Team for Body Check LLC
Body Check, LLC provides AI-powered, HIPAA-secure cardiovascular risk assessment imaging solutions for healthcare professionals. Their platform focuses on analysing medical imaging data to help detect and assess cardiovascular risks with high accuracy.
Target Platform:
Web
Outcome Framework
Services We Provided
01
Project Lead
Managed all client-facing communication, oversaw project delivery, and ensured feedback was effectively channelled between the team and Body Check LLC. This single point of contact kept annotators and QA focused on execution.
02
Annotators (×2)
Responsible for annotating the assigned dataset with a focus on quality and consistency. Their output fed directly into the QA review stage before client delivery.
03
QA Specialist
Annotated alongside the team and conducted a thorough review of all completed work within MD.ai before delivery — acting as the final checkpoint to ensure accuracy and compliance with client standards.
How Structured Coordination Ensured Delivery
Clear, non-overlapping responsibilities kept the project moving without bottlenecks. The Project Lead absorbed all client communication overhead, freeing the annotation team to focus solely on quality. A built-in QA checkpoint ensured no work reached the client without validation — reducing error risk and maintaining consistent delivery standards throughout the engagement.
Outcome
Note: The annotations delivered by our team directly supported Body Check LLC's FDA submission - validating the precision and clinical reliability of our annotation workflow for high-stakes medical imaging. Completed annotations were verified by an expert radiologist through MD.ai's built-in QA workflow. Body Check LLC additionally provided positive acknowledgement of annotation quality via email, confirming alignment with clinical and regulatory standards.
Challenges & How We Addressed Them
Anatomical Complexity & Precision
Structures such as cardiac calcifications, liver boundaries, and vertebral-level body composition demanded high accuracy. Rigorous training and client reference materials guided annotators through complex and ambiguous cases.
Image Quality Variability
CT scan differences in contrast, resolution, and slice thickness affected segmentation consistency. SOPs set clear guidelines, while team collaboration and regular client feedback refined approaches to difficult scans.
Operational & Workflow Efficiency
Delivering high-quality annotations across multiple time-sensitive projects required strict coordination. Structured training and regular client check-ins kept quality high without sacrificing delivery timelines.
Quality Assurance Process
Quality was embedded at every stage of the workflow — not treated as an afterthought. The QA Specialist reviewed all annotator output within MD.ai before delivery, ensuring consistency and accuracy. An expert radiologist at Body Check LLC conducted final verification, providing an additional layer of clinical oversight. Client feedback loops were maintained throughout the project to catch and resolve ambiguities early.
CONCLUSION
This engagement demonstrates how a well-structured, specialised annotation team can deliver measurable impact in high-stakes medical imaging projects. By combining clear role definitions, rigorous QA processes, and continuous client collaboration, our team successfully supported Body Check LLC through one of the most demanding milestones in healthcare AI development — FDA submission. The team also ensured that delivery standards were the same on the first day, although the technicalities of 3D segmentation, anatomical precision, and inconsistent quality of CT scans were present. The inherent quality assurance checkpoint, skilled radiologist verification, and systematic SOPs were used to make sure that all the annotations were per clinical and regulatory expectations. The collaboration with Body Check LLC indicates our belief in offering annotation services that will be over and above being accurate, which will be reliable, transparent, and operationally disciplined to navigate regulatory procedures with the necessary confidence of the healthcare AI companies. The team also ensured that delivery standards were the same on the first day, although the technicalities of 3D segmentation, anatomical precision, and inconsistent quality of CT scans