Medical imaging AI
Models are the easy part. Getting them into the imaging workflow — reliably, safely, measurably — is the work.
Overview
Imaging AI is an integration problem as much as a model problem
A model that performs well in a study delivers nothing until it sits inside the imaging workflow, receives studies reliably, and writes results somewhere a radiologist actually looks.
Imaging AI
- Model integration
- Triage & prioritisation
- Detection & measurement support
- Quantitative imaging
- Longitudinal comparison
Workflow
- Modality worklist integration
- PACS & VNA integration
- DICOM / DICOMweb
- Structured reporting
- Zero-footprint viewing
Governance
- Model validation
- Performance monitoring
- Drift detection
- Version control
- Audit trails
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Put a model into the workflow.
Integration, validation and monitoring for imaging AI.