Medical University of Vienna

The MUW is one of Europe’s most prestigious research and medical training institutions. The Computational Imaging Research Lab at the Department of Biomedical Imaging and Image-guided Therapy is an interdisciplinary research group with strong medical, computer science and mathematical background. The group’s goal is to understand how to extract relevant knowledge from medical images to support medical research and to apply computer vision methods in the diagnosis and monitoring of diseases. The biomedical imaging department has extensive experience in performing research on large-scale clinical imaging data. The computational imaging research lab (CIR) is an interdisciplinary research division at the interface of medical imaging and machine learning.  In several projects, MUW developed computational imaging biomarkers covering clinical fields from breast, lung and brain imaging and has proven their ability to bring AI and clinical routine together.

Role of institution in the project

MUW will contribute to research and development across the project with a focus on the bridging to the clinical community, and the development of methodology in the area of continual machine learning and cancer imaging.

Prof. Georg Langs

Prof. Georg Langs is Director of the Computational Imaging Research Lab at the Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria. He is a mathematician, whose research focusses on machine learning methodology in the area of image analysis models to predict individual disease course and treatment response.

Prof. Helmut Prosch

Prof. Helmut Prosch is Section Chief of Thoracic Imaging at the Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria. His research focuses on the diagnosis and staging of lung cancer and on deep learning for the diagnosis of diffuse parenchymal lung diseases. He serves as Deputy Editor of the journal European Radiology. Prof. Prosch has published more than 200 articles, reviews and book chapters.

Dr. Philipp Seeböck

Dr. Philipp Seeböck has a strong record in deep learning and medical image analysis, particularly in anomaly detection to disentangle healthy from abnormal variability, domain adaptation, representation learning and patient outcome prediction.

Dr. Pamela Zolda

Dr. Pamela Zolda is a research manager with over 15 years of experience in research and infrastructure projects. She has successfully coordinated FP7 and H2020 projects and led dissemination activities therein. She was also part of the management of the ESFRI project Euro-BioImaging.

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!

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TECHNICAL DEMONSTRATION WEBINAR

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