Tracing of thin tubular structures in computer tomographic data.
For many applications in diagnostics and in the planning of surgical interventions, specific structures have to be identified in a patient's volume data set. In this article we give an outline of how the detection of thin tubular structures (e.g., nerves and vessels) can be automated, requiring very little initialization from a human expert. We focused on the nervus alveolaris inferior in the lower jaw and were looking at three details: data acquisition, detection, and validation of accuracy. Our method can be easily adapted to many similar cases such as other nerves, arteries, and veins or bundles thereof.
Department of Oral and Maxillofacial Surgery, University of Heidelberg, Germany. v97@ix.urz.uni-heidelberg.de
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W
Stein
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Hassfeld
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J
Muhling
D000465:Algorithms; D000792:Angiography / Q000379:methods*; D001331:Automation; D006801:Humans; D008334:Mandible / Q000000981:diagnostic imaging / Q000294:innervation; D008340:Mandibular Nerve / Q000000981:diagnostic imaging; D010347:Patient Care Planning; D010525:Peripheral Nerves / Q000000981:diagnostic imaging*; D010690:Phlebography; D011856:Radiographic Image Enhancement / Q000379:methods*; D015203:Reproducibility of Results; D014057:Tomography, X-Ray Computed / Q000379:methods*