Image Registration

Image registration is the process of finding a spatial alignment between two images depicting the same or similar scenes. It allows for the fusion of images from different modalities and time points and therefore is an important prerequisite for multimodal diagnostics. Highly specialized algorithms tackle particular registration problems, but they are often only available in specialized research settings; they lack standardized operating environments and independent validation.

The image registration project focuses on several topics that are strongly interconnected. We develop specific registration algorithms, e.g. for lung, prostate, head-neck or paraspinal images involving cancer. A software module for the easy integration of image registration algorithms into a rapid-prototyping platform makes these algorithms available for all applications developed using this platform. Our generic translational registration platform MatchPoint serves as a coordination layer between our algorithms and other applications.

Contact: Ralf O. Floca, Clemens Hentschke, Andreas Jäger, Dörte Corr


For information about RTToolbox, see this page

Contact: Lanlan Zhang, Ralf O. Floca


In fractionated radiotherapy monitoring the treatment course of a patient is essential to produce the best possible therapy. Setup errors caused through positioning errors or random errors caused by organ motion are two examples which can lead to deviation errors between the prescribed dose and the actual applied dose. Furthermore, geometrical uncertainties of the tumor make larger safety margins necessary. Monitoring the patients geometrical and dosimetrical variances aid physicians to define compensation strategies.

This work will present a software framework, which allows monitoring geometrical and dosimetrical variances. To analyze geometrical changes of a specific patient or body structure, image registration methods are necessary to address the fact that evaluation of an image registration method has to be done for a specific domain. Thus, an evaluation strategy is presented to quantify the quality of a specific image registration method and to ensure consistent and valid results. To assist specialist in the decision process, graphical result representations are automatically generated for specific time points of a single therapy or for a study. To assist in retrospective analysis in clinical studies, the framework presents graphical data illustration for complete patient collections.

Contact: Andreas Jäger

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