Oslo University Hospital

Oslo University Hospital is Scandinavia’s largest hospital serving 2.7 million people (~50% of Norway) with a total employment base of approximately 20,000 employees. The hospital carries out advanced patient treatment, research and trial treatments, give advice and provide education on international levels. Oslo University Hospital is an emergency hospital for East and Southern Norway and have national emergency assignments.The hospital is responsible for approximately 50 percent of all medical and healthcare research conducted at Norwegian hospitals and is a significant role player within the education of a large variety of health care personnel. with special focus in emergency care, organ transplantation, cardiology, cancer, immunology, stem cell research, molecular biology and neurological research.

Role of institution in the project

The institution has invested significant resources into establishing the infrastructure needed for a large-scale radiology-focused artificial intelligence lab. The core of this lab is an in-house GPU server park with necessary IT infrastructure for modern machine learning development, model training and big data management. Through our in-house platform radiologists, clinicians and researchers’ have direct access to data and deployment of AI models.

The institution will provide a federated node for hosting local data in accordance with EUCAIM’s interfaces and specifications. This includes registering prepared datasets of specific projects in the EUCAIM’s Metadata catalogue, as well as offering local processing capabilities.

Kyrre Eeg Emblem

Chair of the Department of Physics and Computational Radiology. Clinic for radiology and nuclear medicine. Group leader MRI Research & Technology

Prof. Atle Bjørnerud

Head of Computational Radiology & Artificial Intelligence (CRAI) Unit. Department of Physics and Computational Radiology. Clinic for radiology and nuclear medicine

Jon E. Nesvold

TechLead, Computational Radiology & Artificial Intelligence (CRAI). Department of Physics and Computational Radiology. Clinic for radiology and nuclear medicine

Bradley J MacIntosh

Senior Scientist, Computational Radiology & Artificial Intelligence (CRAI). Department of Physics and Computational Radiology. Clinic for radiology and nuclear medicine

Join the EUCAIM Consortium

Open Call for New Beneficiaries

We’re inviting new partners to enhance our pan-European infrastructure for cancer images and artificial intelligence.

Whether you’re a data holder with valuable cancer images or an innovator developing AI tools for precision medicine, this is your chance to contribute to a groundbreaking project.

Apply by 10 June 2024!

Open Call Webinar

We recently hosted a webinar with more details for prospective applicants to the open call. A recording is available.

Our open Call for new collaborators
launches in April 2024

Opportunities for data holders & AI developers to contribute await! Let‘s join forces to enhance cancer diagnosis and treatment

Be the first to know and apply!

SAVE THE DATE
March 14, 10:00-11:30 aM CET

DISCOVER THE CANCER IMAGE EUROPE PLATFORM

TECHNICAL DEMONSTRATION WEBINAR

Explore the potential for AI-driven cancer care advancements!
Learn how to access and utilize our federated cancer image repository. The webinar is for AI Innovators & Data Providers interested in the platform and will feature an introduction to EUCAIM & Cancer Image Europe and a demonstration of data exploration & access.

Survey Invitation

Join Leading Experts In Shaping AI In Cancer

EUCAIM is looking for your feedback! We have recently published a Stakeholder Survey in order to reach out to potential end-users and stakeholders. We believe that your insights could significantly contribute to understanding the expectations of potential users and identifying the essential aspects that stakeholders find crucial for future engagement and collaboration with the platform.

Therefore, we would like to invite you to participate in the Stakeholder Survey about the Cancer Image Europe platform.

Completing the survey will take approximately 10 minutes. Your participation is crucial to the success of this project, and we deeply appreciate your expertise in shaping the future of cancer imaging and treatment.