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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)

Annual Report

Mon Jun 26 21:22:20 GMT 2000