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2026 – Munich, Germany / Trondheim, Norway — Researchers from Norwegian University of Science and Technology (NTNU), Norway’s largest public research university and a central driver of national healthcare innovation, are working with deepc to fast-track the clinical translation of medical imaging AI. The collaboration reflects a shared focus on enabling the validation and clinical deployment of locally developed medical AI, in line with Norway’s healthcare priorities and regulatory frameworks, while continuing innovation across the Nordic region.
The central focus of this partnership is PROVIZ, an AI model developed at NTNU to improve prostate cancer diagnostics using magnetic resonance imaging (MRI). Prostate cancer affects approximately one in eight men during their lifetime, with cases expected to rise as populations age and PSA testing increases. While MRI is now a key component of prostate cancer diagnostics, interpretation remains highly dependent on manual assessment by experienced radiologists, making the process resource-intensive and limiting the use of quantitative imaging data.
PROVIZ is designed to address these challenges by providing radiologists with transparent and interpretable AI-driven decision support. The system combines deep learning, model-based imaging features, and clinical information to support more accurate and efficient detection of clinically significant prostate cancers, and improved targeting of prostate biopsies. The project is built on a diverse dataset of more than 2,000 existing prostate MRIs, supported by an interdisciplinary research team with expertise in MRI, artificial intelligence, urology, and radiology, and complemented by international collaborations to address demographic and multi-centre variability.
Funded by the Research Council of Norway and embedded within the Centre for Digital Life Norway, PROVIZ is also supported by NTNU Technology Transfer Office (NTNU TTO). PROVIZ has completed proof-of-technology clinical testing at St. Olavs University Hospital (Trondheim) with strong performance. It is now scheduled to enter national or broader multi-centre clinical trials. Moving from AI research into national or international clinical evaluation requires a robust infrastructure that supports regulatory readiness, controlled deployment, performance monitoring, and scalability across clinical environments.
deepc will support NTNU through the deepcOS® Researcher Suite, part of the deepcOS® clinical AI infrastructure platform. The platform enables clinical AI teams to manage the lifecycle of their in-house AI solutions, seamlessly enabling them to deploy, validate, and monitor their solutions directly within real-world clinical workflows. Through deepcOS®, researchers can evaluate PROVIZ across multi-site, multi-centre clinical datasets, including international cohorts, deploy the model in controlled clinical settings, and monitor performance over time, using the same infrastructure that supports enterprise-grade clinical AI deployments.
deepc brings extensive experience in deploying AI solutions into routine clinical practice globally. The company has supported hospitals and medical AI developers in addressing regulatory requirements, data protection obligations, enterprise IT integration, and long-term governance.
Dr. Gabriel Addio Nketiah, Technical and Translational Lead of PROVIZ at NTNU, added: “Medical AI is a strategic priority for Norway, and PROVIZ represents our commitment to developing clinically meaningful AI solutions that are transparent, interpretable, and explainable –built on a diverse dataset and local expertise. Partnering with deepc provides us with the infrastructure needed to support broader clinical trials and future deployment, ensuring that our AI models can be evaluated rigorously and integrated safely into clinical workflows.”
“Too often, high-quality medical AI research struggles to reach patients because the infrastructure required for clinical deployment is complex and fragmented,” said Dr. Franz Pfister, CEO and Co-Founder of deepc. “Our collaboration with NTNU and PROVIZ reflects a shared ambition to remove these barriers and support local innovation that aligns with national healthcare goals. By providing a robust, production-ready AI infrastructure, we help ensure that promising research like PROVIZ can be evaluated, governed, and deployed responsibly within Norway’s healthcare system.”
Through this partnership, NTNU and deepc define an infrastructure-led approach for how academic medical AI research can be translated into clinical practice in a structured, scalable, secure, and regulated manner. The collaboration highlights the role of infrastructure in enabling responsible medical AI adoption and supports Norway’s broader ambition to advance healthcare innovation for the benefit of patients, clinicians, and the healthcare system across the Nordic region.
About deepc
deepc enables the infrastructure layer that powers safe, vendor-neutral AI in medical imaging. Our platform, deepcOS®, spans the full product lifecycle: discovery, clinical validation, deployment, monitoring, and governance, so hospitals can adopt, scale, and continuously improve the AI tools that matter most to their workflows. Through rigorous, large-scale testing on independent and local datasets, deepc certifies every integrated algorithm for performance, robustness, and regulatory compliance. Clinicians can then easily activate best-in-class solutions across more than 80 indications, confident that patient safety and data privacy are protected by design. deepcOS® installs quickly and interfaces seamlessly with existing PACS/RIS, cloud, or on-prem environments. By abstracting complexity and preserving choice, deepc empowers radiology departments to build and evolve an AI-driven practice—faster, safer, and on their own terms today and into the future.
About Norwegian University of Science and Technology (NTNU)
NTNU is Norway’s largest public research university and a key national driver of healthcare innovation. PROVIZ was developed by the Cancer Imaging & Multi-Omics Research (CIMORe) group within NTNU’s Department of Circulation and Medical Imaging, based at NTNU’s main campus in Trondheim.
Led by Prof. Tone Frost Bathen, CIMORe is an interdisciplinary research group with expertise in medical physics, molecular biology, medicine, bioinformatics, pharmacy, chemistry, and machine learning. The group maintains strong ties to clinical practice through long-standing collaboration with St. Olavs University Hospital in Trondheim, supporting translation of research insights into clinical practice and patient care.
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