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Dr. Volker Daum

Alumnus of the Pattern Recognition Lab of the Friedrich-Alexander-Universität Erlangen-Nürnberg

To make the information contained in different imaging modalities and multiple acquisitions useable for the improvement of medical diagnosis as well as (semi-)automatic segmentation and classification.

BMBF Molecular Imaging in Medicine


Mechanism of targeting - Angiogenesis for diagnostics and and therapy

General Project Aim

Inhibition of tumor angiogenesis is emerging as promising target in the treatment of
malignancies. Although anti-angiogenic agents have been shown to be effective in preclinical
models, in clinical trials they were not as successfull as expected necessitating novel tools
for the planning and follow up of antiangiogenic therapy. Therefore, molecular imaging of
angiogenesis is essential for tumour diagnostics and therapy.

In order to streamline the development of molecular imaging probes and drugs of tumour
angiogenesis a highly trans-disciplinary and inter-faculty approach will integrate the required
disciplines in basic and clinical science. The scientific work comprises basic projects dealing
with identification and labelling of novel ligands for angiogenesis related receptors and
preclinical application of these molecules in different tumour models. This is complemented
by correlative imaging with PET and MRI and the development of novel image processing
algorithms for an optimized analysis of imaging data.

The project consortium is composed of


Contribution of the Pattern Recognition Lab

Most of this project is concerned with developing, testing and evaluating molecular tumor angiongenesis markers. Although some part of this is done in vitro the main work is done with in vivo experiments, using small animals (mice, rats) and small animal imaging. While the development of PET markers is one of the focuses, other imaging modalities like CT and MR are also important as they can be used to judge marker specificity, as well as general tumour growth and location.

The Pattern Recognition Lab contributes in these small animal imaging areas its expertise in multimodal medical image registration (rigid and nonrigid), segmentation and general image processing and analysis. Small animal imaging poses its own specific challenges in these application areas due to the small size of the subjects and the correspondingly needed high resolution imaging devices. Currently there is a lack of specialized software for visualizing, processing and analyzing these kind of images. The Pattern Recognition Lab develops tools and a software environment to use for these tasks.