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KVAL: A neural network-based image denoising software

Awarded: NOK 0.46 mill.

Project Number:


Project Period:

2023 - 2023

Funding received from:



Throughout 2023, with the backing of the Qualification fund, we transformed a complex, AI-based software from a prototype running on an inventor's personal computer into a scalable, cloud-based SaaS solution. This evolution has made it broadly accessible and commercially viable. Our integration of GPU acceleration and a user-friendly interface design has rendered the SaaS solution both powerful and easy to navigate for a diverse user base. A key aspect of this commercial project involved market analysis and maintaining close ties with potential customers. Feedback from MRI experts was instrumental in refining our prototype to align with the practical demands of the industry. We conducted comprehensive testing across various imaging techniques, including 3D and 2D microscopy and MRI. The results were encouraging, signifying a significant advancement in image denoising technology. In anticipation of launching a startup, we strategically deliberated over crucial aspects such as location, funding, core team and structure, also exploring potential collaborations to foster future growth. In conclusion, we have successfully completed all the work packages outlined for this commercial project. We are thrilled to have achieved remarkable development in our AI denoising product, elevating its Technology Readiness Level (TRL) from 3 to 5/6. This sets a solid foundation for establishing a spinout company in 2024.

The allocated funding has enabled us to successfully reach all our milestones. We have optimized and fine-tuned our image denoising software-as-a-service (SaaS), preparing it for commercialization. This tool significantly enhances the clarity of medical images for healthcare professionals, offering superior resolution compared to existing solutions. Our solution effectively improves a wide range of medical imaging types, including MRI, CT, X-ray, and microscopy images, ensuring a marked improvement in image quality.

Funding scheme: