Spotlights: A Robust Method for Surface-Based Registration in Orthopedic Surgery

Abstract

Abstract. Fast, simple and effective registration methods are needed in a wide variety of computer-assisted surgical procedures in which readily locatable anatomical landmarks are not available. Surface-based leastsquares registration methods can be used, but are susceptible to poor initial pose estimates and to error contamination during intraoperative data collection. We have developed a fast, statistically robust method for surface-based registration during orthopedic surgery. The method, based on the iterative closest point (ICP) algorithm, fits a set of sparsely measured data points to a planar facet model. A first registration estimate is obtained by having the user contact the anatomy in a set of general anatomical regions (rather than contacting distinctive features). A small number of additional data points are acquired to refine the registration. Starting from the refined estimate, a robust scored perturbation method is used to find a better registration. This is followed by an M-estimate registration that is taken as the final registration. Simulation results show that this method is robust for data sets containing up to 25% gross outliers. The method has been tested in vitro on plastic bone models, where it outperformed the least-squares estimate and maintained the required 1mm/2• accuracy. The in vivo use of spotlights in computer-enhanced osteotomies of the knee have confirmed the usefulness of the method.

Gradient-based 2-D/3-D rigid registration of fluoroscopic X-ray to CT

“…Removal of outliers can be either explicit [24] or implicit by weighing the paired features [25]. Algorithms for geometry-based point to CT registration include the iterative closest point (ICP) algorithm [23], [24] and its variations [25], [28]- [30]. X-ray contours to CT surface mesh algorithms have been developed by Hamadeh et al [9], [11] and Guéziec et al [13], [26].…”

Predicting Target Vessel Location for Improved Planning of Robot-Assisted CABG Procedures

“…Considering that the anastomosis target site is typically located along the LAD path two thirds of the way from the ostia towards the apex, we have implemented a more robust apex localization approach from the US data which led to improved target registration error near the inferior end of the LAD. The new algorithm uses the apical region as a registration constraint as opposed to a single point, and include a robust estimator to reduce the TRE, as suggested by Ma et al [11].…”

Fixation-Based Surgery: A New Technique for Distal Radius Osteotomy

“…We used a robust registration method to estimate the rigid-body transformation from the anatomy to the preoperative data [10]. While the patient was being anesthetized, the surgeon selected initial-estimate landmarks ("spotlights").…”