Fast, accurate surface acquisition using a laser range scanner for image-guided liver surgery

摘要

Many image guided surgical (IGS) procedures use surface representations of anatomical features to provide a registration between physical space and image space. While anatomical fiducial registration techniques can often be compromised by soft tissue deformation, laser-scanning systems offer a non-contact method for accurately resolving geometric surfaces. This digitization approach is particularly well suited for liver resection surgery, where registration is accomplished by aligning the segmented preoperative liver image volume with the intraoperative presentation of the organ. Further, this three-dimensional technology affords a method of rapid surface data acquisition that can be used for the measurement and compensation of tissue deformation. A phantom was constructed to assess the laser scanner's capability of acquiring accurate shape information and robust surface registration. The phantom contained a wealth of point and surface geometry that could be identified in both a CT image volume and a range scan image. Point based registrations were calculated and served as a reference transformation for comparison of the results from surface registration using the iterative closest point (ICP) algorithm, The laser range scanner used the optical principle of triangulation to obtain a dense point set of surface data with a grid spacing of 0.6 mm. The scanner was able to localize and track fiducials on the order of 0.1mm. Phantom experiments demonstrated the ability to perform point-based registrations to CT with a Fiducial Registration Error of 0.5 mm. The scanner accurately resolves geometric surface information and achieved surface-based registrations within a mean distance residual of 0.4 mm. The principal sources of error were systemic misrepresentations of the position by the range scanner, which can be accounted for through calibration or other procedures. The laser scanner system was successfully used to register images to sub-millimetric accuracy. Future work involves acquisition of liver surfaces during surgical procedures for use in registration and deformation measurements.