Cochlea modelling: clinical challenges and tubular extraction
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
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Various anatomical objects are tubular in shape. These structures can be modeled by describing their curvilinear path and the cross-sectional shape along the path. However, most research on tubular object segmentation has focused on vascular systems, and often assumes a circular cross-section. These techniques are not readily applicable to anatomy such as the cochlea, which has a non-circular cross-sectional shape. We present the Principal Flow Filter, which calculates the flow vector (tangential to the path) in a local region of a tubular object with a non-circular cross-section. It can be used to extract the centerline orientation and thus incrementally track along the tube. We present results from generated data with a variety of cross-sectional shapes. The filter is shown to rapidly and robustly converge to the true orientation. We also analyse a CT scan of a human cochlea, with promising results.