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BMBF Molecular Imaging in Medicine (MoBiMed) - Mechanism of targeting, Angiogenesis for diagnostics and and therapyThe project consortium is concerned with the research of the imaging of
tumor angiogenesis. To that end specific tumor markers that can be used
in molecular imaging are developed by the clinical project partners.
Research is performed mostly on small animals (mouse, rat) and with multimodal
imaging techniques to evaluate and analyze tumor growth and marker specificity. In this project the pattern recognition lab develops
algorithms and a software environment for use in multimodal (PET, CT,
MR), small animal imaging. Standard algorithms have to be adjusted
to the specific challenges in small animal imaging, arising from
the small subject size. The work focuses on registration and
segmenation techniques. Image registration techniques allow to correlate different modalities,
such that for example marker specificity to the tumor region can be
easily evaluated. Both rigid and non-rigid registration algorithms are
currently under development. The rigid registration is focusing on speed,
accuracy and robustness with respect to transforms that contain only
rotations and translations. The nonrigid registration calculates a free
form transform, which allows for a direct pixel-by-pixel comparison of
the registered images. Segmentation techniques that are currently investigated are mostly
semi-automatic. This allows the user to specify roughly the regions
of interest that are then automatically refined by the algorithm. The
Random Walk algorithm has been implemented, to facilitate easy and fast
segmentation. The algorithm is hardware accelerated on the graphics
hardware (GPU) and can yield a segmentation in less than 5 seconds. Future work will mostly focus on adapting existing algorithms to
small animal imaging. In cooperation with the Department of Nuclear
Medicine it is planned to identify useful workflows for the
evaluation of PET marker performances. These workflows can then
be supported by specifically developed software tools.
| Project manager: Prof. Dr.-Ing. Joachim Hornegger, Prof. Dr. med. Torsten Kuwert
Project participants: Dr. Volker Daum, Dr.-Ing. Dieter Hahn, Prof. Dr. rer. nat. Olaf Prante
Keywords: segmentation; registration; small animal imaging; angiogenesis
Duration: 1.1.2009 - 31.12.2012
Mitwirkende Institutionen: Nuklearmedizinische Klinik, Universitätsklinikum Erlangen Radiologische Klinik und Poliklinik Universitätsklinikum Heidelberg Deutsches Krebsforschungszentrum Klinik und Poliklinik für Nuklearmedizin, Universitätsklinikum Münster European Institute for Molecular Imaging (EIMI) Diagnostische und Interventionelle Radiologie, Universitätsklinikum Tübingen
| Publications |
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Hahn, Dieter ; Daum, Volker ; : Automatic Parameter Selection for Multi-Modal Image Registration. In: IEEE Transactions on Medical Imaging 29 (2010), No. 5, pp 1140-1155 | Hahn, Dieter ; Daum, Volker ; ; Kuwert, Torsten: Data-Driven Density Estimation applied to SPECT Subtraction Imaging for Epilepsy Diagnosis. In: Wells, William ; Joshi, Sarang ; Pohl, Kilian (Org.) : Proceedings of the MICCAI Workshop on Probabilistic Models For Medical Image Analysis (Medical Image Computing and Computer-Assisted Intervention - MICCAI 2009, 12th International Conference London, UK 20.09.2009). 2009, pp 115-126. | Daum, Volker ; Hahn, Dieter ; ; Kuwert, Torsten: PCA Regularized Nonrigid Registration for PET/MRI Attenuation Correction. In: Wells, William ; Joshi, Sarang ; Pohl, Kilian (Org.) : Proceedings of the MICCAI Workshop on Probabilistic Models For Medical Image Analysis (Medical Image Computing and Computer-Assisted Intervention - MICCAI 2009, 12th International Conference London, UK 20.09.2009). 2009, pp 127-138. |
Institution: Chair of Computer Science 5 (Pattern Recognition)
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