Medizinische Universität Wien

Medical University of Vienna (MedUni Vienna) is one of the longest-established medical education and research facilities in Europe. With almost 8,000 students, it is currently the largest medical training centre in the German-speaking countries. With more than 6,000 employees, 30 departments and two clinical institutes, 12 medical theory centres and numerous highly specialised laboratories, it is one of Europe’s leading research establishments in the biomedical sector.

The MUW Computational Imaging Research (CIR) lab is an interdisciplinary research group of scientists from medicine, computer science and mathematics. It is a division of the Department of Biomedical Imaging and Image-guided Therapy at the Medical University of Vienna conducting research at the interface of medical imaging, machine learning, and precision medicine. Its goal is to understand how to extract relevant knowledge from medical images, to model the relationship between images and biological mechanisms, and to develop methods for predicting individual disease course and treatment response. CIR lab is an international interdisciplinary team with colleagues of diverse backgrounds joining projects with impact in science and patient care.

Research at CIR is grouped around several intersecting research lines. The lab is investigating machine learning approaches to analyse lung imaging data ranging from prediction models to unsupervised techniques to identify phenotypes in large scale populations and studying fetal brain development based on in-utero magnetic resonance imaging data with a focus on modelling structural- and functional changes during gestation. It maps the functional organisation of the human brain based on functional magnetic resonance imaging (fMRI) in healthy as well as diseased adults. Identifying anomalies is a way to expand the vocabulary of imaging markers, that can be used for diagnosis and prediction. The CI lab studies approaches based on generative deep learning models to detect anomalies, and translates them into disease markers. CIR also develops deep learning approaches to deal with varying image appearance across institutes and time, methodologically related to continual learning, domain adaptation and learning disentangled representations.

The Division of Cardiovascular and Interventional Radiology at the Department of Bioimaging and Image-Guided Therapy at the Medical University Vienna is focused on the diagnosis and treatment of cardiovascular diseases. A clear focus of scientific, educational and clinical work is on cardiac and vascular imaging as well as on the diagnosis and endovascular, minimal-invasive treatment of aortic diseases, as well as in the endovascular therapy of ischemic stroke. The staff consists on 11 staff physicians (Radiologists), 5 Radiology Residents, 2 research technicians, 2 study coordinators, and a variable number of PhD students. 

The division is the leading center for modern cardiovascular diagnosis in Austria representing the reference center for education, training and research in this modern field. In close relation and collaboration with our clinical partners, mainly form Cardiology and Cardiac surgery, we are continuously working on improving the patient care in cardiovascular diseases. Our staff member are involved in the leadership of  the relevant medical societies and organizations (ESR, ESOR, ESCR, and more)

 

Role in the project

MUW leads WP3 Explainabel AI Models for Prediciton and significantly contribute to WP2. In WP2, providing in-depth knowledge, experience, as well as clinical data in and about cardiac CT obtained at the newest scanner generation, the photon-counting CT scanner Naeotom Alpha, MUW will co-develop optimized imaging strategies and ptorocols, to establish usable workflow for post-processing and analysis of the clincial CT data, to interact closely with software providers as well as with the other clinical sites. Within WP3, MUW will lead the developmen of an AI-POD risk score to predict individual risk of adverse cardiac events in obese people and will provide restrospective and prospective imaging data as the basis for the development of truthworthy AI.

Team

Ulrike I. Attenberger

Prof. Dr. Ulrike I. Attenberger is Head of the Clinical Division of General and Paediatric Radiology at the Department of Biomedical Imaging and Image-guided Therapy at the Medical University of Vienna. In 2005, she graduated from Medical School at the Ludwig-Maximilians University (LMU) in Munich, Germany. At the same time, she worked on her doctorate thesis focusing on the role of MRI in the diagnostics of pulmonary hypertension. After a residency in the Institute of Clinical Radiology of the Klinikum Grosshadern (LMU Munich) and the Department of Radiology and Nuclear Medicine of the University Medical Center Mannheim, Ulrike I. Attenberger became vice chair of the Department of Radiology and Nuclear Medicine of the University Medical Center Mannheim. In 2019, she became Chair and Director of the Clinic for Diagnostic and Interventional Radiology at Bonn University Hospital. She held this position until she moved to the Medical University of Vienna on July 15, 2024. She is particularly interested in the introduction of AI techniques for quantitative disease characterization and the development of imaging-based biomarkers. Ulrike I. Attenberger participates in many different committees, such as the Scientific Advisory Board of the German Medical Association. Furthermore, she contributed to more than 200 scientific articles, reviews, and book chapters

Georg Langs
Georg Langs is the founding director of the Computational Imaging Research Lab (CIR) at the Medical University of Vienna. CIR is an interdisciplinary research group of ~30 researchers. His research interests are in the development of machine learning approaches at the interface of medical imaging, precision medicine, and neuroscience. He has been PI, work package leader, and Site-PI for national and internationally funded projects. He serves as director of the EIBIR Joint Initiative AI in Medical Imaging, on the core planning team of the UNO-IAEA-WHO-FAO initiated Zoonotic Disease Integrated Action(ZODIAC), is Member of the Taskforce Digitalization in Health Care of the Walter Siegenthaler Gesellschaft, and Associate Faculty at the Complexity Science Hub Vienna.
 

Georg Langs is co-coordinator of the PhD-Programme Medical Imaging, and lecturer at Medical University of Vienna, University of Vienna, Ecole Centrale de Paris, and Vienna University of Technology, and was Host and Co-Organizer of BrainHacks Vienna Reproducibility and Repeatability in Neuroimaging(2016), and Evolution and Development(2019), Co-Organizer at NIPS’11-NIPS’16: MLINI Workshop. Georg Langs has been elected into the IS3R Emerging Leaders Club, the National Academy of Medicine(USA) Emerging Leader Programme, and is member of the European Society of Radiology and the Austrian Society for Artificial Intelligence.

Christian Loewe

Christian Loewe is the chairman of the Division of Cardiovascular and Interventional Radiology, Department of Bioimaging and Image-Guided Therapy at the Medical University of Vienna, Austria.
He is the president of the Austrian Rontgen Society), as well as member of the executive committee of the European Society of Cardiovascular Radiology and member of the Executive Council of the European Society of Radiology (ESR).

He is especially interested  in postgraduate education in Austria and in Europe. For 6 years, he chaired the European Board of Cardiovascular Radiology, and for 10 years, he chaired the Austrian Board Examination in Radiology. He serves as a member of the Steering Committee of the European School of Radiology (ESOR).
He was member of the Editorial Board of European Radiology (2002 – 2011) and Associate Editor of Radiology (2011 – 2017), and is currently Consultant to the Editor (Radiology). Since 2020, Christian Loewe is Deputy Editor of Insights Into Imaging (I3).
The main focus of his clinical and scientific work includes noninvasive cardiovascular diagnostic imaging as well as diagnosis and treatment of aortic diseases. He gave more than 400 invited lectures, has authored and co-authored more than 160 articles in peer-reviewed journals.

Philipp Seeböck

Philipp Seeböck is a postdoctoral research scientist in the CIR lab at the Medical University of Vienna (MUV), with a background in computer science. After completing his PhD in the field of medical image analysis and deep learning, he was head of IT at the Vienna Reading Center (VRC) from 2019 to 2022, simultaneously working as a postdoc at the Department of Ophthalmology. He is active in teaching and supervision, and co-organizer of the CVPR 2023 Workshop “VAND: Visual Anomaly and Novelty Detection”. P. Seeböck is also a member of the European Radiology Scientific Editorial Board and 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.

 

Pamela Zolda

Pamela Zolda holds a phD in biology and prior to joining MUW worked as university assistant at the University of Vienna and European research manager in an international research organization, where she worked closely with the Scientific Leadership and all bodies at strategic and operational levels. She has more than a decade of experience in writing, coordinating and managing international imaging projects and recruiting organizations for project consortia (FP7, H2020, Horizon Europe). Pamela also was part of the founding group of the large-scale research infrastructure Euro-BioImaging. Currently she leads project management and dissemination efforts in several projects at national an EU level.

 

Dietrich Beitzke

Priv. Doz. Dr. Dietrich Beitzke obtained his medical degree at the Medical University of Graz, Austria. After a general medical education in Graz and his residency in radiology in Graz and Vienna he became board certified radiologist in 2014. Since then he acts head of the cardiovascular MR Unit at the Medical University of Vienna.
In clinical routine Dr. Beitzke covers the whole spectrum of non-invasive Cardiovasular Imaging by CT, CMR and hybrid imaging. His scientific focus is on vascular inflammation and non-invasive imaging in the follow up after cardiac transplant. So far Dr. Beitzke has published and co-authored 80+ papers in peer reviewed journals in the field of cardiology and radiology.

 

Anastasia Bartashova

Anastasia Bartashova is an experienced radiographer focussed on cardiovascular imaging and was part of the computed tomography department at the General Hosipital in Vienna (AKH Wien). Additionally, with more than five years of experience and a Master’s degree in project management-entrepreneurship, she is now member of the AI-POD project, where she is responsible for coordinating the study at the Medical University of Vienna (MUW). With an ongoing Master’s degree in Public Health (MUW), she offers a combination of expertise in the field of radiological technology and health promotion, to support the project in the long run.

Benedikt Heidinger

Benedikt Heidinger serves as an attending radiologist with a special interest at the Medical University of Vienna in cardiothoracic imaging. He earned his medical degree from the Medical University of Vienna, before completing a three-year post-doctoral research fellowship in Cardiothoracic Imaging at Harvard Medical School / Beth Israel Deaconess Medical Center in Boston, USA. In 2016, Benedikt was awarded the prestigious Sven Paulin Research Fellowship in Cardiothoracic Imaging at the Harvard Medical School. Moreover, he holds a PhD in cardiopulmonary disease. He joined the Department of Biomedical Imaging and Image-guided Therapy at the Medical University of Vienna, Austria, as resident in radiology in 2018 and obtained his Austrian along with his European board certificate in 2023.

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