Research interests

The study of complex cellular processes (e.g., cell division, virus infection) based on high-content screening techniques requires to analyze large amounts of image data. Because of the enormous increase in the generation of 2D, 3D, and 4D microscopy images a manual evaluation is no longer possible and a computer-based analysis is necessary. On the other hand, in the field of molecular cell biology, it becomes more and more important to derive quantitative information about the shape, motion, and function of cellular as well as subcellular structures as a prerequisite for computational modelling in systems biology (e.g., reconstruction of pathways). In our group, we are developing methods and algorithms for computer-based analysis of biological and medical images, in particular, multidimensional and multichannel fluorescence cell microscopy images. Main research topics are the segmentation and quantification of cellular structures, the localization and tracking of cellular and viral structures, and the geometric alignment of image data (image registration) for the pupose of image normalization. A particular focus is on efficient and reliable image analysis approaches for the quantification of siRNAi high-throughput screens, and on approaches for high-accuracy localization, tracking, and registration. We closely collaborate with other biomedical research groups, for example, at the EMBL Heidelberg, the DKFZ (German Cancer Research Center), the LMU Munich, the Research Center Jülich, the BIOQUANT center of the University of Heidelberg, the University Hospital Heidelberg, and international partners (France, The Netherlands, USA, Korea).
Homepage: http://www.bioquant.uni-heidelberg.de/bmcv

 

Methods applied

We develop methods within the field of biomedical image analysis and microscopy image analysis. The focus is on model-based approaches for quantitative imaging. The spectrum of methods comprises image-based segmentation, supervised classification, model-based localization, probabilistic tracking, as well as spline-based and optic flow-based elastic registration."