Image-Based Biomedical Modeling
In the Focus Group "Image-based Biomedical Modeling" Rudolf Mößbauer Tenure Track Professor Bjoern Menze and his group explore topics at the interface of medical computer vision, image-based modeling and computational physiology. In this, they primarily deal with applications in clinical neuroimaging and the modeling of tumor growth. Their work strives towards transforming the descriptive interpretation of biomedical images into a model-driven analysis that infers properties of the underlying physiological and patho-physiological processes by using models from biophysics and computational physiology. A related effort is the application of such models to big data bases in order to learn about correlations between model features and disease patterns at a population scale.
Current projects follow two main lines of research:
The first direction is the modeling of processes underlying images acquired in common diseases of the brain. The focus is on the analysis of images acquired in glioma and stroke patients, including the development of algorithms for the longitudinal analysis of brain lesions using parametric and non-parametric lesion evolution models, and the quantitative interpretation of blood flow patterns at population scale. The main sources of information are multimodal and multi-parametric clinical image data sets featuring MR, PET and CT scans.
The second direction deals with the task of optimal oncological staging. It includes the anatomical annotation of large field of view images – such as abdominal scans or whole body images – the detection of lesion across modalities and in repeated scans, and the analysis of individual lesion using descriptive pathophysiological models.
Emphasis is put on the clinical applicability, and algorithms are supposed to scale well to large data sets enabling the development of population wide disease progression models.
TUM-IAS funded doctoral candidate:
Esther Alberts, Computer-Aided Medical Procedures & Augmented Reality / Neuroradiology
Jana Lipkova, Computer-Aided Medical Procedures & Augmented Reality
Markus Rempfler, Computer-Aided Medical Procedures & Augmented Reality
Dr. Vasileios Zografos, Computer Aided Medical Procedures & Augmented Reality