In this work a fully automated detection method for artery input function (AIF) and venous output function (VOF) in 4D-computer tomography (4D-CT) data is presented based on unsupervised classification of the
time intensity curves (TIC) as input data. Bone and air voxels are first masked out using thresholding of the
baseline measurement. The TICs for each remaining voxel are converted to time-concentration-curves (TCC)
by subtracting the baseline value from the TIC. Then, an unsupervised K-means classifier is applied to each
TCC with an area under the curve (AUC) larger than 95% of the maximum AUC of all TCCs. The results are
three clusters, which yield average TCCs for vein and artery voxels in the brain, respectively. A third cluster
generally represents a vessel outside the brain. The algorithm was applied to five 4D-CT patient data who were
scanned on the suspicion of ischemic stroke. For all _ve patients, the algorithm yields reasonable classification
of arteries and veins as well as reasonable and reproducible AIFs and VOF. To our knowledge, this is the first
application of an unsupervised classification method to automatically identify arteries and veins in 4D-CT data.
Preliminary results show the feasibility of using K-means clustering for the purpose of artery-vein detection in
4D-CT patient data.
User interaction during navigated surgery is often a critical issue in the overall procedure, as several complex aspects
must be considered, such as sterility, workflow, field of view, and cognitive load. This work introduces a new approach
for intraoperative interaction that seamlessly fits the high surgical requirements. A navigation system, typically
consisting of a tracking system and a monitor for 3D virtual models, is augmented with a tracked pointer with triggering
functionality and a pan-tilt mounted laser. The pointer, which is sterile and can be applied for landmark-based organ
registration, is used for wireless interaction with the monitor scene. The laser system enables the calibration of the
monitor, which is out of the tracking system's range. Moreover, the laser beam can focus on any organ point defined on
the virtual model, which improves targeting or visual feedback during intervention. The calibration of the laser system,
monitor, and triggered pointer is achieved by an effective procedure, which can be easily repeated in operating room. The
mathematical background of the calibration is based on the Levenberg-Marquardt and Umeyama's algorithms.
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