Challenge landscape
Case StudiesHemoScan
Case Study
ImagingHemoScan
CT hemorrhage detection AI
AI-powered CT hemorrhage detection system supporting radiology triage and rapid identification of time-sensitive intracranial findings.
CT AIClinical Decision SupportDICOMImaging TriageIntracranial Hemorrhage
softx.ca · hemoscan
Scan Details
JointKnee
StatusAnalyzed
Confidence98%
AI Overlays
Heatmap
Landmarks
Contours
AI Assisted
Frame 4/12
Context
The Problem
Critical intracranial hemorrhages can be missed or delayed in high-volume CT workflows, creating triage bottlenecks and slower time-to-action.
- Intracranial bleed detection
- imaging triage
Approach
The Solution
CT hemorrhage detection AI that flags time-sensitive findings and supports imaging triage within radiology workflows.
- DICOM
- PACS integration
- optional RIS hooks
- API endpoints for results and prioritization.
Implementation approach
Delivery
How We Built It
Clinical workflow mapping → dataset curation & labeling → model development → validation/QA → DICOM/PACS integration → deployment with monitoring and feedback loop.
Outcomes
Results
CT AI
Clinical Decision Support
DICOM
Imaging Triage
Intracranial Hemorrhage
Model Monitoring
On-Prem
PACS