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School of Life Sciences
and Facility Management

Research Group Medical Image Analysis & Data Modeling

Upper left: rendering of segmented intracranial aneurysm (vessel dilation); bottom: extraction pipeline of aneurysm segmentation and analysis; upper right: network model, where different variables (e.g., age, disease status) interact and follow probability distributions.

Introduction

Technological advances and the ongoing digitalization in healthcare are driving the systematic collection of medical data ever further. This data offers the opportunity to better understand diseases, support clinical decision making with evidence, and optimize medical processes.

Biomedical imaging is among the primary sources of information for many clinical applications and scientific endeavors. Its data-intensive nature necessitates dedicated algorithmic methods to process the images and uncover the information hidden within.

In addition to imaging data, a myriad of clinically relevant parameters is collected on patients, to monitor their health status, to describe pathologies, or to document physiological boundary conditions. Modeling of medical data using e.g., statistical models and inference enables disease prediction and increases understanding of pathomechanisms. Such data-based models are desired to be interpretable to serve as evidence-based tools in clinical practice.

The research group covers the whole range of medical data handling: from data acquisition to data processing and modeling. The goal of the group’s applied research is to translate data-based methods into clinical practice to the benefit of medical staff and ultimately patients.

 

Expertise

The research group has expertise and experience in:

  • Biomedical imaging: magnetic resonance imaging, computed tomography, histological imaging
  • Computer vision: image processing & analysis
  • Machine learning & deep learning
  • Bayesian inference & modeling
  • Integration of domain knowledge: medical expertise, crowdsourcing of expert knowledge

Areas of application

Together with our collaborators we strive to solve problems via our applied and translational research. Various medical domains are covered, mainly:

 

Cooperation with partners

We collaborate in various projects with academic, clinical and industry partners. Such local, national, and international institutions are:

 

Engagement in teaching

The members of the research group are involved in various teaching activities. Most notably, we are lecturing and supervising student projects/theses in the following programs:

 

Team