Level-Set Surface Segmentation
and Fast Cortical Range Image Tracking for Computing Intra-surgical Deformations
We have proposed a method for estimating intra-surgical brain shift for
image-guided surgery, which consists of five stages: 1) the identification
of relevant anatomical surfaces within the MRI/CT volume, 2) range-sensing
of the skin and cortex in the OR (operating room), 3) rigid registration
of the skin range image with its MRI/CT homologue, 4) non-rigid motion
tracking over time of cortical range images, and 5) interpolation of this
surface displacement information over the whole brain volume via a realistically
valued finite element model of the head. The surface identification scheme
implements 3D surface segmentation as the level-set of a 4D moving front.
A by-product of this stage is a Euclidean distance and closest point map,
which is later exploited to speed up the rigid and non-rigid registration.
The method has been validated with a novel deformable brain-shaped phantom,
made of Polyvinyl Alcohol Cryogel.
M. A. Audette (Montreal Neurological Institute, McGill University),
K. Siddiqi, T. M. Peters (Robarts Research Institute)
Mon Jun 26 21:22:20 GMT 2000