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Dipl.-Inf. Dime Vitanovski

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

Robust patient-specific dynamic model detection for intervention planning

Using a Wireless Motion Controller for 3D Medical Image Catheter Interaction

State-of-the-art morphological imaging techniques usually provide high resolution 3D images with a huge number of slices. In clinical practice, however, 2D slice-based examinations are still the method of choice even for these large amounts of data. Providing intuitive interaction methods for specific 3D medical visualization applications is therefore a critical feature for clinical imaging applications. For the domain of catheter navigation and surgery planning, it is crucial to assist the physician with appropriate visualization techniques, such as 3D segmentation maps, fly-through cameras or virtual interaction approaches. There has been an ongoing development and improvement for controllers that help to interact with 3D environments in the domain of computer games. These controllers are based on both motion and infrared sensors and are typically used to detect 3D position and orientation. We have investigated how a state-of-the-art wireless motion sensor controller (Wiimote), developed by Nintendo, can be used for catheter navigation and planning purposes. By default the Wiimote controller only measure rough acceleration over a range of +/- 3g with 10% sensitivity and orientation. Therefore, a pose estimation algorithm was developed for computing accurate position and orientation in 3D space regarding 4 Infrared LEDs. Current results show that for the translation it is possible to obtain a mean error of (0.38cm, 0.41cm, 4.94cm) and for the rotation (0.16, 0.28) respectively. Within this paper we introduce a clinical prototype that allows steering of a virtual fly-through camera attached to the catheter tip by the Wii controller on basis of a segmented vessel tree.