Title :
Cortical surface registration for image-guided neurosurgery using laser-range scanning
Author :
Miga, Michael I. ; Sinha, Tuhin K. ; Cash, David M. ; Galloway, Robert L. ; Weil, Robert J.
Author_Institution :
Dept. of Biomed. Eng., Vanderbilt Univ., Nashville, TN, USA
Abstract :
In this paper, a method of acquiring intraoperative data using a laser range scanner (LRS) is presented within the context of model-updated image-guided surgery. Registering textured point clouds generated by the LRS to tomographic data is explored using established point-based and surface techniques as well as a novel method that incorporates geometry and intensity information via mutual information (SurfaceMI). Phantom registration studies were performed to examine accuracy and robustness for each framework. In addition, an in vivo registration is performed to demonstrate feasibility of the data acquisition system in the operating room. Results indicate that SurfaceMI performed better in many cases than point-based (PBR) and iterative closest point (ICP) methods for registration of textured point clouds. Mean target registration error (TRE) for simulated deep tissue targets in a phantom were 1.0 ± 0.2,2.0 ± 0.3, and 1.2 ± 0.3 mm for PBR, ICP, and SurfaceMI, respectively. With regard to in vivo registration, the mean TRE of vessel contour points for each framework was 1.9 ± 1.0, 0.9 ± 0.6, and 1.3 ± 0.5 for PBR, ICP, and SurfaceMI, respectively. The methods discussed in this paper in conjunction with the quantitative data provide impetus for using LRS technology within the model-updated image-guided surgery framework.
Keywords :
brain; image texture; laser applications in medicine; medical image processing; phantoms; surgery; cortical surface registration; data acquisition system; image-guided neurosurgery; in vivo registration; iterative closest point method; laser-range scanning; model-updated image-guided surgery framework; mutual information; operating room; phantom registration studies; point-based method; simulated deep tissue targets; textured point clouds; vessel contour points; Bioreactors; Clouds; Imaging phantoms; In vivo; Iterative closest point algorithm; Laser modes; Neurosurgery; Surface emitting lasers; Surface texture; Surgery; Adult; Algorithms; Brain Neoplasms; Cerebral Cortex; Feasibility Studies; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Intraoperative Care; Lasers; Male; Neurosurgical Procedures; Reproducibility of Results; Sensitivity and Specificity; Stereotaxic Techniques; Subtraction Technique; Surgery, Computer-Assisted;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2003.815868