Real-time Correction Scheme for Calibration and Implementation of Microscope-based Image-guided Neurosurgery

摘要

Microscope-based image-guided neurosurgery can be divided into three steps: calibration of the microscope optics; registration of the pre-operative images to the operating space; and tracking of the patient and microscope over time. Critical to this overall system is the temporal retention of accurate camera calibration. Classic calibration algorithms are routinely employed to find both intrinsic and extrinsic camera parameters. The accuracy of this calibration, however, is quickly compromised due to the complexity of the operating room. the long duration of a surgical procedure, and the inaccuracies in the tracking system. To compensate for the changing conditions, we have developed an adaptive procedure which responds to accruing registration error. The approach utilizes miniature fiducial markers implanted on the bony rim of the craniotomy site, which remain in the field of view of the operating microscope. A simple error function that enforces the registration of the known fiducial markers is used to update the extrinsic camera parameters. The error function is minimized using a gradient descent. This correction procedure reduces RMS registration errors for cortical features on the surface of the brain by an average of 72%, or 1.5 mm. These errors were reduced to less than 0.6 mm after each correction during the entire surgical procedure.