Cortical surface characterization using a laser range scanner for neurosurgery

Abstract

This dissertation covers research regarding the use of laser range scanning (LRS) during neurosurgery. Impetus for this work stems from the desire to provide relevant intraoperative data regarding the position and motion of the brain relative to preoperative image tomograms. LRS provides an excellent technology for providing fast, accurate, and well-resolved surface data of the exposed brain. Methods described in this dissertation represent a novel visualization system capable of providing real-time cortical surface characterization. More specifically, techniques have been developed that register intraoperative LRS data to preoperative MR tomograms and quantify the motion of the brain using serial LRS acquisitions. The results generated from these techniques are presented as graphical renderings that provide correspondence between the exposed cortical surface and anatomical structures in the preoperative tomograms. In vivo validation shows that cortical surface registration and motion tracking can be achieved to millimetric accuracy. The impact of these results allows enhanced recognition of cortical structures while providing meaningful assessment of brain deformation during surgery. In summary, this research provides a comprehensive examination of LRS for use within the operating theater and constitutes a significant step toward the use of intraoperative cortical surface data in image-guided neuronavigation.