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Prof. Dr. Anja Hennemuth


Charité – Universitätsmedizin Berlin

Augustenburger Platz 1, D-13353 Berlin

Prof. Dr. Anja Hennemuth


Fellow | BIFOLD

Professor for Image-based Therapy Support | Institute for Cardiovascular Computer-assisted Medicine, Charité – Universitätsmedizin Berlin

Member of Management Board | Fraunhofer MEVIS

2020 3rd Place EMIDEC Classification Challenge at MICCAI 2020
2017 Best Paper Award at the conference Functional Imaging and Modeling of the Heart
2015 KUKA Best Paper Award at the conference for Computer-assisted Radiology and Surgery
2014 Fraunhofer Talenta Excellence Program
2011 Elsevier Best Paper Award at the conference Medical Image Computing and Computer Assisted Interventions
2000 sd&m Scholarship

  • Medical Image Computing
  • Image-based Therapy Support
  • Clinical Decision Support
  • Image-based Modeling
  • Machine Learning in Medical Image Processing

  • GI

Hinrich Rahlfs, Markus Hüllebrand, Sebastian Schmitter, Christoph Strecker, Andreas Harloff, Anja Hennemuth

Learning carotid vessel wall segmentation in black blood MRI using sparsely sampled cross-sections from 3D data

April 03, 2024

Johanna Brosig, Nina Krüger, Isaac Wamala, Matthias Ivantsits, Simon Sündermann, Jörg Kempfert, Stefan Heldmann, Anja Hennemuth

Learning 3D aortic root assessment based on sparse annotations

April 03, 2024

Antonia Popp, Alaa Abd El Al, Marie Hoffmann, Ann Laube, Peter McGranaghan, Volkmar Falk, Anja Hennemuth, Alexander Meyer

Segment-wise Evaluation in X-ray Angiography Stenosis Detection

February 20, 2024

Tabea Kossen, Manuel Alexander Hirzel, Vince Istvan Madai, Franziska Boenisch, Anja Hennemuth, Kristian Hildebrand, Sebastian Pokutta, Kartikey Sharma, Adam Hilbert, Jan Sobesky, Ivana Galinovic, Ahmed Abdelrahim Khalil, Jochen B Fiebach, Dietmar Frey

Toward sharing brain images: Differentially private TOF-MRA images with segmentation labels using generative adversarial networks

May 02, 2022

Anja Hennemuth, Markus Hüllebrand, Patrick Doeblin, Nina Krüger, Sebastian Kelle

Anwendungen von künstlicher Intelligenz in der diagnostischen kardialen Bildanalyse

March 21, 2022

BIFOLD Update| Aug 06, 2020

An overview of the current state of research in BIFOLD

Since the official announcement of the Berlin Institute for the Foundations of Learning and Data in January 2020, BIFOLD researchers achieved a wide array of advancements in the domains of Machine Learning and Big Data Management as well as in a variety of application areas by developing new Systems and creating impactfull publications. The following summary provides an overview of recent research activities and successes.