Nasal-Skull Base Fast Path Extraction and Automatic Navigation

In the nasal-skull base virtual endoscope, the existing navigation path extraction algorithms have low operation efficiency, and automatic navigation algorithm is easy to cause violent rotation of image. Therefore, a center path extraction algorithm based on navigation area pre-planning and an automatic navigation algorithm based on adaptive speed and rotation are proposed. The former improves the distance transformation method. The navigation area is pre-planned based on the fast expanding random tree and calculate the boundary distance field map, and construct the maximum cost tree to extract the center path. The latter improves the DoTween method. The camera moving speed is adjusted according to the length of the shortest line segment in the path, and the predicted steering distance is adjusted according to the cavity diameter at the vertex in the path. Experiments are conducted with nasal models from DICOM. The results show that the path extraction speed of the center path extraction algorithm based on navigation area pre-planning method is about 49 times faster than the distance transformation method, and the automatic navigation algorithm of adaptive speed and rotation is more natural at the vertices comparing with methods such as DoTween.