ITEA is the Eureka Cluster on software innovation
ITEA is the Eureka Cluster on software innovation
Published on 30 Apr 2024

IVVES project featured as case study in PMI report ‘Navigating AI in Project Management’ and in PMI Podcast

PMI report ‘Navigating AI in Project Management’

In today's rapidly evolving business landscape, the integration of artificial intelligence (AI) into project management has become a game-changer for many organisations, driving efficiency, enhancing decision-making, and fostering innovation.

To inspire the project management community to explore the advantages of integrating AI into their project management practices, the Swedish Chapter of PMI, the leading authority in project management, published the report ’Navigating AI in Project Management’. This report also features the ITEA project IVVES as one of twelve case studies in which project managers share the challenges and opportunities presented by implementing AI-driven processes within their project management frameworks.

The IVVES (Industrial-grade Verification and Validation of Evolving Systems) project developed approaches for robust and comprehensive, industrial-grade verification and validation of embedded AI, i.e. machine-learning for control of complex, mission-critical evolving systems and services covering the major industrial domains in Europe. It brought together application owners from transportation, finance, healthcare, industrial automation, and cybersecurity, with tool developers and AI researchers.

Implementing AI to benefit MR Imaging

Award-winning ITEA project IVVES

IVVES project leader Mark van Helvoort from Philips explains that in the healthcare application, Philips identified that reducing reconstruction times and obtaining better image quality in image reconstruction in Magnetic Resonance Imaging was necessary, as MRI is a relatively slow imaging method. In addition, the threat of adverse images in image recognition was a challenge in a highly regulated environment for a critical application. Philips believed that AI could be a key piece of the solution.

To replace conventional image reconstruction based on the time-consuming Fast Fourier Transform (FFT) method, machine learning models were created which transform the digitised electrical signals into pictures. These pictures can then further be enhanced through noise reduction or image resolution. The implementation of verification and validation was straightforward because all machine learning models were frozen before the start of verification, from a legal perspective the market introduction could therefore be addressed as for products without AI. Overall, the implementation of AI in MR Imaging resulted in better images created in a shorter time, benefiting healthcare providers and their patients.

More information

If you are interested in IVVES or one of the other case studies, or if you would like to learn more about integrating AI into your project management practices, you can download the complete report via

PM Untold Podcast 'Managing AI Projects'

PMI Podcast Managing AI projects

Mark van Helvoort also featured in the PM Untold Podcast 'Managing AI Projects', created by the collaboration of PMI Belgium, Netherlands and Luxembourg, where Mark tells more about implementing AI and the IVVES project. You can listen to the Podcast here:

More information about the IVVES project: and