Clinical Experience with a Hich Precision Image-Guided Neurosurgery System

We describe an image-guided neurosurgery system which we have successfully used on 70 cases in the operating room. The system is designed to achieve high positional accuracy with a simple and efficient interface that interferes little with the operating room’s usual procedures, but is general enough to use on a wide range of cases. It uses data from a laser scanner or a trackable probe to register segmented MR imagery to the patient’s position in the operating room, and an optical tracking system to track head motion and localize medical instruments. Output visualizations for the surgeon consist of an “enhanced reality display,” showing location of hidden internal structures, and an instrument tracking display, showing the location of instruments in the context of the MR imagery. Initial assessment of the system in the operating room indicates a high degree of robustness and accuracy.

[1]  P. Cinquin,et al.  Computer assisted medical interventions , 1995 .

[2]  Richard J. Evans,et al.  Development and preliminary evaluation of VISLAN, a surgical planning and guidance system using intra-operative video imaging , 1996, Medical Image Anal..

[3]  Tomas Lozano-Perez,et al.  An automatic registration method for frameless stereotaxy, image guided surgery, and enhanced reality visualization , 1996 .

[4]  Demetri Terzopoulos,et al.  Medical Image Segmentation Using Topologically Adaptable Snakes , 1995, CVRMed.

[5]  Dietrich Meyer-Ebrecht,et al.  An Optical Navigator for Brain Surgery , 1996, Computer.

[6]  Terry M. Peters,et al.  Three-dimensional multimodal image-guidance for neurosurgery , 1996, IEEE Trans. Medical Imaging.

[7]  S. James Zinreich,et al.  An optical 3D digitizer for frameless stereotactic surgery , 1996, IEEE Computer Graphics and Applications.

[8]  W. Eric L. Grimson,et al.  Adaptive Segmentation of MRI Data , 1995, CVRMed.

[9]  W. Eric L. Grimson,et al.  Experimentation with a transcranial magnetic stimulation system for functional brain mapping , 1998, Medical Image Anal..

[10]  Gil J. Ettinger.  Hierarchical three-dimensional medical image registration , 1997 .

[11]  W. Eric L. Grimson,et al.  Adaptive Segmentation of MRI Data , 1995, CVRMed.

[12]  C. Pelizzari,et al.  Frameless stereotaxy with real-time tracking of patient head movement and retrospective patient-image registration. , 1996, Journal of neurosurgery.

[13]  Berthold K. P. Horn,et al.  Closed-form solution of absolute orientation using unit quaternions , 1987 .

[14]  G. Marchal,et al.  Multi-modal volume registration by maximization of mutual information , 1997 .

[15]  W. Eric L. Grimson,et al.  Segmentation of Brain Tissue from MR Images , 1995, CVRMed.

[16]  Guido Gerig,et al.  Segmentation of 3D Objects from MRI Volume Data Using Constrained Elastic Deformations of Flexible Fourier Surface Models , 1995, CVRMed.

[17]  G. Holmes,et al.  Three-dimensional reconstruction and surgical navigation in pediatric epilepsy surgery. , 1997 .

[18]  R Kikinis,et al.  Automatic identification of gray matter structures from MRI to improve the segmentation of white matter lesions. , 1995, Journal of image guided surgery.

[19]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[20]  W. Eric L. Grimson,et al.  Evaluating and Validating an Automated Registration System for Enhanced Reality Visualization in Surgery , 1995, CVRMed.

[21]  Max A. Viergever,et al.  Probabilistic Hyperstack Segmentation of MR Brain Data , 1995, CVRMed.