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The new generation of multislice computed tomography (CT) scanners allows for the acquisition of high-resolution images of the heart. Based on that image data, the heart can be analyzed in a noninvasive way-improving the diagnosis of cardiovascular malfunctions on one hand, and the planning of an eventually necessary intervention on the other. One important parameter for the evaluation of the severeness of a coronary artery disease is the number and localization of calcifications (hard plaques). This work presents a method for localizing these calcifications by employing a newly developed vessel segmentation approach. This extraction technique has been developed for, and tested with, contrast-enhanced CT data sets of the heart. The algorithm provides enough information to compute the vessel diameter along the extracted segment. An approach for automatically detecting calcified regions that combines diameter information and gray value analysis is presented. In addition, specially adapted methods for the visualization of these analysis results are described.

Subject motion appears to be a limiting factor in numerous magnetic resonance imaging (MRI) applications. For head imaging the subject's ability to maintain the same head position for a considerable period of time places restrictions on the total acquisition time. For healthy individuals this time typically does not exceed 10 minutes and may be considerably reduced in case of pathology. In particular, head tremor, which often accompanies stroke, may render certain high-resolution 2D and 3D techniques inapplicable. Several navigator techniques have been proposed to circumvent the subject motion problem. The most suitable for head imaging appears to be the orbital or spherical navigator methods. Navigators, however, not only lengthen the measurement because of the time required for acquisition of the position information, but also require additional excitation radio frequency (RF) pulses to be incorporated into the sequence timing, which disturbs the steady state. Here we demonstrate the possibility of interfacing the MR scanner with an external optical motion tracking system, capable of determining the object's position with sub-millimeter accuracy and an update rate of 60Hz. The movement information on the object position (head) is used to compensate the motion in real time. This is done by updating the field of view (FOV) by recalculating the gradients and the RF-parameter of the MRI tomograph during the acquisition of k-space data based on the tracking data. Results of rotation phantom, in vivo experiments and the implementation in two different MRI sequences are presented.

Brachytherapy is the treatment method of choice for patients with a tumor relapse after a radiation therapy with external beams or tumors in regions with sensitive surrounding organs-at-risk, e. g. prostate tumors. The standard needle implantation procedure in brachytherapy uses pre-operatively acquired image data displayed as slices on a monitor beneath the operation table. Since this information allows only a rough orientation for the surgeon, the position of the needles has to be verified repeatedly during the intervention. Within the project Medarpa a transparent display being the core component of a medical Augmented Reality (AR) system has been developed. There, pre-operatively acquired image data is displayed together with the position of the tracked instrument allowing a navigated implantation of the brachytherapy needles. The surgeon is enabled to see the anatomical information as well as the virtual instrument in front of the operation area. Thus, the Medarpa system serves as 'window into the patient'. This paper deals with the results of first clinical trials of the system. Phantoms have been used for evaluating the achieved accuracy of the needle implantation. This has been done by comparing the output of the system (instrument positions relative to the phantom) with the real positions of the needles measured by means of a verification CT scan.