Cloud based software solution for super-resolution imaging

The introduction of super-resolution proved to be one of the greatest advances in microscopy the last decades. Super-resolution technologies are still young and pose disadvantages with their speed, quality, and cost. Through a decade of research, utilization of AI, and close collaboration with the microscopy industry, we present the super-resolution technique MUSICAL as a modern solution outmatching any commercial solution in terms of cost and flexibility, while maintaining speed and quality. MUSICAL is currently available through a cloud-based solution coined MUSIcloud, which has been the core solution in this project. The main objective with this project was to finalize our commercialization strategy and reduce risks assosicated with market placement and technology implementation for the industry. Throughout the project we have evaluated our commercial potential and risks, and have together with our commercial consultant and an SME in the micoscopy domain achieved to establish a commercial strategy for MUSIcloud.

Outcome: MUSICAL and the solution MUSIcloud has been a core focus for the inventors at UiT the last decade. Through the project the project participants have greatly improved their understanding for commercialization of research based innovations. Furthermore, all project participants and their institutions have been in close dialog with several industry players. Strenghtening our presence and network with the microscopy market and industry. This has also boosted the understanding of academic work going forward and how to focus on innovation if relevant in such work. Impact: MUSIcloud is an easy and affordable super-resolution imaging software. High quality imaging will no longer be restricted behind cost and specialized training. With higher accessability of super-resolution imaging we can expect a burst in R&D in such field as Life Science and Pathology, advancing new discoveries and medicines. The solution has been validated by industry players, approving it's image processing capabilities and demonstrating it in a relevant environment.