Laboratory Investigations Techniques for Fast and Accurate Intrasurgical Registration

The goal of intrasurgical registration is to establish a common reference frame be- tween presurgical and intrasurgical three-dimensional data sets that correspond to the same anatomy. This paper presents two novel techniques that have application to this problem, high-speed pose tracking and intrasurgical data selection. In the first part of this paper, we describe an approach for tracking the pose of arbitrarily shaped rigid objects at rates up to 10 Hz. Static accuracies on the order of 1 nun in translation and 1" in rotation have been achieved. We have demonstrated the technique on a human face using a high-speed VLSI range sensor; however, the technique is independent of the sensor used or the anatomy tracked. In the second part of this paper, we describe a general purpose approach for selecting near-optimal intrasurgical registration data. Because of the high costs of acqui- sition of htrasurgical data, our goal is to minimize the amount of data acquired while ensuring regis- tration accuracy. We synthesize near-optimal intrasurgical data sets, based on an analysis of differential surface properties of presurgical data. We demonstrate, using data from a human femur, that dis- crete-point data sets selected using our method are superior to those selected by human experts in terms of the resulting pose-refinement accuracy. J Image Guid Surg 2:27-29 (2995)). 01995 Wiley-Liss, Inc. ~

[1]  Takeo Kanade,et al.  A VISI Smart Sensor For Fast Range Imaging , 1992, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Robert M. Haralick,et al.  2D-3D pose estimation , 1988, [1988 Proceedings] 9th International Conference on Pattern Recognition.

[3]  M. Hebert,et al.  The Representation, Recognition, and Locating of 3-D Objects , 1986 .

[4]  P Munger,et al.  Comparison of relative accuracy between a mechanical and an optical position tracker for image-guided neurosurgery. , 1995, Journal of image guided surgery.

[5]  Nicholas Ayache,et al.  Smoothing and Matching of 3-D Space Curves , 1992, ECCV.

[6]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  P. Cinquin,et al.  Computer-assisted spine surgery: a technique for accurate transpedicular screw fixation using CT data and a 3-D optical localizer. , 1995, Journal of image guided surgery.

[8]  Naokazu Yokoya,et al.  A Robust Method for Registration and Segmentation of Multiple Range Images , 1995, Comput. Vis. Image Underst..

[9]  Peter Kazanzides,et al.  An image-directed robotic system for precise orthopaedic surgery , 1994, IEEE Trans. Robotics Autom..

[10]  Takeo Kanade,et al.  Real-time 3-D pose estimation using a high-speed range sensor , 1993, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[11]  Marc Rioux,et al.  Direct Estimation of Range Flow on Deformable Shape From a Video Rate Range Camera , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Takeo Kanade,et al.  Towards More Capable and Less Invasive Robotic Surgery in Orthopaedics , 1995, CVRMed.

[13]  Jon Louis Bentley,et al.  Multidimensional binary search trees used for associative searching , 1975, CACM.

[14]  Jon Louis Bentley,et al.  An Algorithm for Finding Best Matches in Logarithmic Expected Time , 1977, TOMS.

[15]  Shree K. Nayar,et al.  Real-time focus range sensor , 1995, Proceedings of IEEE International Conference on Computer Vision.

[16]  K. Sato,et al.  Range imaging system utilizing nematic liquid crystal mask , 1987 .

[17]  Pradeep K. Khosla,et al.  Dexterity measures for design and control of manipulators , 1991, Proceedings IROS '91:IEEE/RSJ International Workshop on Intelligent Robots and Systems '91.

[18]  S. Hayati,et al.  A robot with improved absolute positioning accuracy for CT guided stereotactic brain surgery , 1988, IEEE Transactions on Biomedical Engineering.

[19]  Richard A. Robb,et al.  New approach to 3-D registration of multimodality medical images by surface matching , 1992, Other Conferences.

[20]  Gabriel Taubin,et al.  Estimation of Planar Curves, Surfaces, and Nonplanar Space Curves Defined by Implicit Equations with Applications to Edge and Range Image Segmentation , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  Jean-Claude Latombe,et al.  Planning for Image-Guided Radiosurgery , 1994 .

[22]  Hong-Tzong Yau,et al.  Automated precision measurement of surface profile in CAD-directed inspection , 1992, IEEE Trans. Robotics Autom..

[23]  Ron Kikinis,et al.  Automated Registration for Enhanced Reality Visualization in Surgery , 1994 .