Title :
Stereopsis-guided brain shift compensation
Author :
Sun, Hai ; Lunn, Karen E. ; Farid, Hany ; Wu, Ziji ; Roberts, David W. ; Hartov, Alex ; Paulsen, Keith D.
Author_Institution :
Dartmouth Med. Sch., Hanover, NH, USA
Abstract :
Brain deformation models have proven to be a powerful tool in compensating for soft tissue deformation during image-guided neurosurgery. The accuracy of these models can be improved by incorporating intraoperative measurements of brain motion. We have designed and implemented a passive intraoperative stereo vision system capable of estimating the three-dimensional shape of the surgical scene in near real-time. This intraoperative shape is compared with the cortical surface in the co-registered preoperative magnetic resonance (MR) volume for the estimation of the cortical motion resulting from the open cranial surgery. The estimated cortical motion is then used to guide a full brain model, which updates a preoperative MR volume. We have found that the stereo vision system is accurate to within approximately 1 mm. Based on data from two representative clinical cases, we show that stereopsis guidance improves the accuracy of brain shift compensation both at and below the cortical surface.
Keywords :
biological tissues; biomechanics; biomedical MRI; brain; deformation; image registration; medical image processing; physiological models; stereo image processing; surgery; brain deformation models; brain motion; co-registered preoperative magnetic resonance volume; image-guided neurosurgery; open cranial surgery; passive intraoperative stereo vision system; soft tissue deformation; stereopsis-guided brain shift compensation; Biological tissues; Brain modeling; Deformable models; Motion estimation; Motion measurement; Neurosurgery; Power system modeling; Shape; Stereo vision; Surgery; Brain deformation; brain modeling; image-guided neurosurgery; stereopsis; Algorithms; Artificial Intelligence; Cerebral Cortex; Computer Simulation; Depth Perception; Female; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Magnetic Resonance Imaging; Male; Middle Aged; Models, Biological; Neuronavigation; Pattern Recognition, Automated; Photogrammetry; Reproducibility of Results; Sensitivity and Specificity; Surgery, Computer-Assisted;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2005.852075