Registration of 3-D surface data for intra-operative guidance and visualization in frameless stereotactic neurosurgery

Abstract

We describe a technique for registering 3-D multimodal image data, acquired preoperatively, with intraoperative surface data derived from stereo video during neurosurgery. Ultimately, our aim is to provide a system that supplants traditional frame-based stereotactic techniques while achieving comparable accuracy. For registration we employ chamfer-matching in conjunction with a cost function that is robust to ' outliers'. To balance robustness and computation speed, we employ a quasi-stochastic search of parameter space that includes pursuing multiple start points. This paper describes the registration problem as it pertains to our application. We discuss our approach to optimization and carry out a computational evaluation of the technique under various conditions.