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Faculty 3 - Mathematics and Computer Science: RG Digital Medicine

RG Digital Medicine

The Digital Medicine Working Group at the University of Bremen is focused on the digital support of diagnosis and therapy. We analyze medical data using data-driven and biophysical models and process the results accordingly to support decision-making. Our goal is to make the daily routine easier for clinical users and to improve the quality of care. To achieve this, we engage in intensive exchanges with various clinical stakeholders who support us with their expertise and clinical data.

Ein Lehrender schreibt an eine Tafel.
© Universität Bremen

Teaching

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Gezeigt wird der Magenbereich schematisch segmentiert mit verschiedenen Strukturen sowie eine Darstellung des segmentierten Gehirns.
© Fraunhofer MEVIS

Research

  • Image & Data Analysis

  • Modelling & Simulation

  • Image Registration

  • Visualization and Interaction

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Contact

RG Digital Medicine

Faculty 3 - Mathematics and Computer Science

Prof. Dr.-Ing. Horst Hahn

Max-von-Laue-Straße 2

28359 Bremen

Telephone: +49 421 218-59002

Email

Office

Marlott Hederich

Telephone: +49 421 218-64430

Email

News

Vergleich von sphärischen Markern gegenüber Tetraeder Markern.
© Erik Immoor
RG Digital Medicine|

Erik Immoor will present his master's thesis at VCBM 2024

Erik Immoor will present his master's thesis "Potential of Tetrahedral Markers for Infrared Pose Tracking in Surgical Navigation" at VCBM 2024 in Magdeburg. His work was accepted as a short paper and will be shown on September 19th at 12:00.

SPIE Medical Imaging Logo
© SPIE
RG Digital Medicine| Pro-Mics-BrCa|

Kai Geißler presents a poster at SPIE Medical Imaging in San Diego

Kai Geißler presented the poster "Deformable current-prior registration of DCE breast MR images on multi-site data" at SPIE Medical Imaging: Image Processing in San Diego. The article demonstrates the registration of follow-up examinations.

Eine Reihe von Zuhörern in einem Seminarraum.
© Universität Bremen
RG Digital Medicine|

Seminar: Deep Learning for Medical Image Processing is being offered again

In the winter semester 2023/2024, we will again offer the seminar: Deep Learning for Medical Image Processing. It will cover a variety of network architectures for different medical applications.

Verschiedene Segmentierungen der Brust auf MRT Daten
© Springer Nature
RG Digital Medicine| Pro-Mics-BrCa|

Ani Ambroladze presents Poster at BVM Workshop

Ani Ambroladze presented the Poster "CNN-Based Whole Breast Segmentation in Longitudinal High-Risk MRI Study" at the BVM 2023 in Braunschweig. It is our first paper in the "Pro-Mics-BrCa" project, showing off the breast segmentation on MRI images.

Updated by: Tom Koller
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