Georg Langs

Full Professor of Machine Learning in Medical Imaging

Medical University of Vienna

Austria

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Research Interests

Medical Imaging

100%

Cognitive Neuroscience

30%

In Vivo Imaging

30%

Neuroscience

30%

Traumatology

20%

Magnetic Resonance Imaging

20%

Learning And Memory

20%

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Positions1

Georg Langs

University Name

Medical University of Vienna

NaN years ago

AI and Medicine

No summary provided for this position.

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Articles19

Identifying signatures of image phenotypes to track treatment response in liver disease

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Year:

2025

Deep-ER: Deep Learning ECCENTRIC Reconstruction for fast high-resolution neurometabolic imaging

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Year:

2025

Deep learning links localized digital pathology phenotypes with transcriptional subtype and patient outcome in glioblastoma

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Year:

2024

Integrated Diagnostics: Embracing Artificial Intelligence and, Above All, Multidisciplinary Teamwork

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Year:

2024

Improving Vessel Segmentation with Multi-Task Learning and Auxiliary Data Available Only During Model Training

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Year:

2024

Contrast Agent Dynamics Determine Radiomics Profiles in Oncologic Imaging

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Year:

2024

Artificial intelligence in medical imaging is a tool for clinical routine and scientific discovery

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Year:

2024

Artificial intelligence in respiratory pandemics—ready for disease X? A scoping review

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Year:

2024

Predicting Outcomes of Preterm Neonates Post Intraventricular Hemorrhage

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Year:

2024

Deep learning for predicting future lesion emergence in high-risk breast MRI screening: a feasibility study

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Year:

2023

Innovations in Deep Learning to Predict Individual Risk and Treatment Outcome

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Year:

2023

Evolution of cortical geometry and its link to function, behaviour and ecology

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Year:

2023

Fetal temporal sulcus depth asymmetry has prognostic value for language development

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Year:

2023

Continual Active Learning Using Pseudo-Domains for Limited Labelling Resources and Changing Acquisition Characteristics

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Year:

2022

Radiomics score predicts acute respiratory distress syndrome based on the initial CT scan after trauma

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Year:

2021

Correction to: Radiomics score predicts acute respiratory distress syndrome based on the initial CT scan after trauma

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Year:

2021

Dynamic memory to alleviate catastrophic forgetting in continual learning with medical imaging

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Year:

2021

Analyzing Longitudinal wb-MRI Data and Clinical Course in a Cohort of Former Smoldering Multiple Myeloma Patients: Connections between MRI Findings and Clinical Progression Patterns

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Year:

2021

Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem

Article Link

Year:

2020

Collaborators14

Hedvig Hricak

Professor

UNITED STATES

Nathan Jeffery

University of Liverpool

UNITED KINGDOM

Priska Bauerstätter

AIT Austrian Institute of Technology GmbH

AUSTRIA

Bernhard Baumann

Associate professor

Medical University of Vienna

AUSTRIA

Adelheid Woehrer

Professor

Medical University of Innsbruck

AUSTRIA

Thomas Roetzer-Pejrimovsky

Medical University of Vienna

AUSTRIA

Lisa Bartha-Doering

Associated Professor; before: Assistent Professor

Medical University of Vienna

AUSTRIA

Martin Rajchl

Imperial College London

UNITED KINGDOM

Benedikt Heidinger

Medical University of Vienna

AUSTRIA

Wolfgang Bogner

Associate Professor

Medical University of Vienna

AUSTRIA

Helmut Prosch

Assoc. Prof.

Medical University of Vienna

AUSTRIA

Marlene Stuempflen

Medical University of Vienna

AUSTRIA

Johanna Klughammer

Associate Professor

Ludwig-Maximilians-Universität München

GERMANY

Pascal A. T. Baltzer

AUSTRIA

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