Over the last years, perfusion imaging has become an important diagnostic tool for stroke and brain tumor patients. In the context of stroke, perfusion is reduced for affected areas, whereas in the context of tumors, perfusion is increased, a result of the tumor neovascularization. In recent years, research has focused on perfusion analysis for abdominal organs, too.

In perfusion CT, a contrast agent is injected into the blood supply for the region of interest and its temporal spreading is analyzed.

Image processing methods are required in order to automatically determine the region of the organ to be studied. This is a challenging task, as different abdominal organs exhibit similar intensities in CT acquisitions, making it difficult to distinguish between individual tissue classes. Additionally, organ movements and deformations, for example due to respiration, have to be compensated through image registration in order to obtain an accurate perfusion analysis.

The goal of this project is to develop image processing methods which are fast, accurate, and robust, and require only a minimum amount of user interaction, in order to meet the requirements for clinical work flows. This research project is supported by our industrial partner Siemens Healthcare.