This video is a quick update on ongoing research at the University of Utah in collaboration with GE Healthcare. The goal in this project is to develop software that can predict the tip of an aspirator going into the head during intra-cranial neurosurgery. The project currently uses the Leap Motion Controller to perform the tracking. Unfortunately, point cloud data cannot currently be extracted directly from the Leap Motion Controller which makes it difficult to define arbitrary object shapes to track. The workaround to this is to predict tip of the tool by finding the position and orientation of both the handle and the orthogonal attachment to the handle (both of these shapes are easily recognized by the controller). A few different attachment configurations have been tried, but this is so far the most successful one.
Surgical Tool Tracking (Update 12/21/13)
