1. Data intake
Normalize DICOM metadata, remove duplicate studies, and preserve audit identifiers before model execution.
Deployment documentation
Practical notes for engineers preparing imaging AI workflows for local validation, review queues, and quality assurance handoff.
2. Model execution
Record model version, input checksum, runtime parameters, and confidence thresholds with every batch.
3. Clinical review
Route outputs to a review queue where overlays, bookmarks, and exception notes remain editable.
Integration checklist
- Confirm study routing policy and retention window.
- Verify TLS termination and access logging for all operator consoles.
- Store model-card version beside each generated output.
- Keep public documentation and internal review systems on separate hosts.
- Run fail-open and fail-closed behavior checks before pilot deployment.
Interface contracts
Reference workflows use simple manifest files for batch transfer. The public package includes an example manifest, checksum list, and release notes for offline review.