Medical Imaging Storage Analyzer
Identify and reduce healthcare imaging data waste, unlocking storage savings and AI readiness.
We partnered to analyze extensive DICOM archives, quantify waste, and provide clear, prioritized recommendations—enhancing performance, reducing costs, and establishing a robust strategy to mitigate the challenges of AI integration in imaging.
The Challenge.
- Massive DICOM archives with up to 75% non‑diagnostic images overwhelming storage.
- Escalating costs and slow transfers caused by data bloat and redundant scans.
- Difficulty preparing imaging data for cloud migration, AI pipelines, and telemedicine.
- Lack of clear insights left IT leaders uncertain how to optimize archives.
The Solution.
- Ran stakeholder interviews, mapped constraints, and validated the vision with a Figma prototype.
- Delivered a responsive web dashboard visualizing storage savings and optimization recommendations.
- Created a HIPAA-compliant Windows desktop scanner and cloud API that analyzed medical imaging archives, uncovered storage inefficiencies, and demonstrated the value of a patented optimization approach.
- Completed UAT, performance tuning, and compliance checks for a smooth production rollout.
Tech Stack
Angular
Tailwind
.NET
Microsoft Entra External ID
Azure Services
SQL Azure
Windows Executable
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