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Client Context
Medical Imaging Early Diagnostic Support for Radiology Workflows
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Industry:
Hospitals / Diagnostic Imaging
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Geography:
India & Middle East
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Engagement Type:
AI-assisted imaging analytics
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Scope:
MRI, CT & X-ray — neuro, chest & musculoskeletal
Challenges
Challenges
- Radiologists experienced high caseload fatigue.
- Subtle abnormal findings were occasionally missed during late-shift reads.
- Report turnaround time (TAT) SLAs were difficult to meet across facilities.
Our Apporach
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Integrated AI-based anomaly detection models into the PACS workflow.
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Prioritized studies with probability of abnormality, enabling load balancing.
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Added structured findings extraction to auto-populate sections of the radiology report.
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Enabled comparison-view models that detect progression vs baseline scan.
Impact Delivered
- Turnaround time improved by 38% for high-priority scans.
- Second-read support reduced miss-risk for subtle findings by 27%.
- Increased radiologist satisfaction and clinical throughput across network hospitals.
30+ years of Industry experience in delivering pioneering data and QA solutions.
