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A system for automatic detection of cephalometric landmarks is presented. Landmark detection is carried out in two steps: a line detection module searches for significant, well-contrasted lines of the image, such as the jaw line or the nasal spine. The landmark detection module uses the lines located in the first module to determine the search areas and then applies a pattern detection algorithm, based on mathematical morphology techniques. Relations between landmarks and lines are determined by means of a training process. The system has been tested for the detection of 17 landmarks on 20 images: more than 90% of the landmarks are accurately identified.

We present a new frameless stereotatic system prototype that has been initially validated in functional neurosurgery operations and that makes use of an optical position tracker for image-guided neurosurgery. Several devices for tracking different surgical instruments have been designed and manufactured. These devices include an array of infrared light-emitting diodes that are tracked by three charge-coupled device cameras. The system presents several new approaches for surgery planning. For high-quality 3D images of the patient’s anatomy, we have developed a parallel version of a volume-rendering algorithm, thus enabling real-time 3D anatomy manipulation on low-cost PC workstations. In order to test the accuracy of the system, the localization of the target by means of a stereotatic frame has been compared with frameless techniques, obtaining a difference of about 1 ± 1 mm.