EdgeOrchestra

EdgeOrchestra

This project designs and evaluates a geo‑distributed orchestration framework for medical image processing across the edge-cloud continuum, enabling dynamic task placement and automatic scaling based on workload. Using tomographic imaging data, the system is experimentally assessed demonstrating the feasibility of edge-cloud medical image computing for future clinical integration.
Cone‑beam CT device scanning an anatomical phantom in a laboratory imaging setup.

Project information

Project duration

-

Funded by

Other Finnish

Project funder

6GESS

Funding amount

30 000 EUR

Project coordinator

University of Oulu

Unit and faculty

Centre for Wireless Communications
Faculty of Information Technology and Electrical Engineering
Research Unit of Health Sciences and Technology
Faculty of Medicine

Contact information

Project leader

Contact person

Researchers

Project description

Medical imaging plays a critical role in modern healthcare by supporting diagnosis and treatment through detailed visualization of internal anatomy and abnormalities. However, traditional workstation‑based systems are increasingly insufficient to meet current demands for mobility, scalability, and cost efficiency.

The edge-cloud continuum offers a promising alternative by distributing virtualized computing components across local, edge, and cloud tiers. This approach enables data processing closer to users and data sources, reducing latency and bandwidth usage while improving scalability and resilience to network disruptions.

This project aligns with broader efforts in digital health innovation, sustainable computing, and the responsible integration of AI into clinical workflows. It provides a strong foundation for future large‑scale collaborations and funding opportunities.