Learn More
Accurate characterization of harmonic tissue motion for realistic tissue geometries and property distributions requires knowledge of the full three-dimensional displacement field because of the asymmetric nature of both the boundaries of the tissue domain and the location of internal mechanical heterogeneities. The implications of this for magnetic(More)
PURPOSE Acquisition of laser range scans of an organ surface has the potential to efficiently provide measurements of geometric changes to soft tissue during a surgical procedure. A laser range scanner design is reported here which has been developed to drive intraoperative updates to conventional image-guided neurosurgery systems. METHODS The scanner is(More)
OBJECTIVE A quantitative analysis of intraoperative cortical shift and deformation was performed to gain a better understanding of the nature and extent of this problem and the resultant loss of spatial accuracy in surgical procedures coregistered to preoperative imaging studies. METHODS Three-dimensional feature tracking and two-dimensional image(More)
Biomechanical models that describe soft tissue deformation provide a relatively inexpensive way to correct registration errors in image-guided neurosurgical systems caused by nonrigid brain shift. Quantifying the factors that cause this deformation to sufficient precision is a challenging task. To circumvent this difficulty, atlas-based methods have been(More)
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(More)
OBJECTIVE Image-guided neurosurgery incorporating preoperatively obtained imaging information is subject to spatial error resulting from intraoperative brain displacement and deformation. A strategy to update preoperative imaging using readily available intraoperative information has been developed and implemented. METHODS Preoperative magnetic resonance(More)
Compensating for intraoperative brain shift using computational models has shown promising results. Since computational time is an important factor during neurosurgery, a priori knowledge of the possible sources of deformation can increase the accuracy of model-updated image-guided systems. In this paper, a strategy to compensate for distributed loading(More)
  • Alexander Hartov, Symma D Eisner, W David, Keith D Roberts, Leah A Paulsen, B S Platenik +1 other
  • 2002
Image-guided neurosurgery that is directed by a preoperative imaging study, such as magnetic resonance (MR) imaging or computerized tomography (CT) scanning, can be very accurate provided no significant changes occur during surgery. A variety of factors known to affect brain tissue movement are not reflected in the preoperative images used for guidance. To(More)
Image-guided liver surgery requires the ability to identify and compensate for soft tissue deformation in the organ. The predeformed state is represented as a complete three-dimensional surface of the organ, while the intraoperative data is a range scan point cloud acquired from the exposed liver surface. The first step is to rigidly align the coordinate(More)
Current brain deformation models have predominantly reflected solid constitutive relationships generated from empirical ex vivo data and have largely overlooked interstitial hydrodynamic effects. In the context of a technique to update images intraoperatively for image-guided neuronavigation, we have developed and quantified the deformation characteristics(More)