A comprehensive system for intraoperative 3D brain deformation recovery.
During neurosurgery, brain deformation renders preoperative images unreliable for localizing pathologic structures. In order to visualize the current brain anatomy, it is necessary to nonrigidly warp these preoperative images to reflect the intraoperative brain. This can be accomplished using a biomechanical model driven by sparse intraoperative information. In this paper, a linear elastic model of the brain is developed which can infer volumetric brain deformation given the cortical surface displacement. This model was tested on both a realistic brain phantom and in vivo, proving its ability to account for large brain deformations. Also, an efficient semiautomatic strategy for preoperative cortical feature detection is outlined, since accurate segmentation of cortical features can aid intraoperative cortical surface tracking.
Department of Biomedical Engineering, Yale University, P.O. Box 208042, New Haven, CT 06520-8042, USA. christine.delorenzo@yale.edu
Christine
C
DeLorenzo
Xenophon
X
Papademetris
Kenneth P
KP
Vives
Dennis D
DD
Spencer
James S
JS
Duncan
D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000033:anatomy & histology* / Q000601:surgery*; D003399:Craniotomy / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D025321:Surgery, Computer-Assisted / Q000379:methods*