Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
International Journal of Computer Vision
Deformation for Image Guided Interventions Using a Three Component Tissue Model
IPMI '97 Proceedings of the 15th International Conference on Information Processing in Medical Imaging
CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
Brain Shift Modeling for Use in Neurosurgery
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Constrained Elastic Surface Nets: Generating Smooth Surfaces from Binary Segmented Data
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Estimation of intraoperative brain surface movement
CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
Tracking Brain Deformations in Time-Sequences of 3D US Images
IPMI '01 Proceedings of the 17th International Conference on Information Processing in Medical Imaging
IPMI '01 Proceedings of the 17th International Conference on Information Processing in Medical Imaging
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part I
Deformable Modeling for Characterizing Biomedical Shape Changes
DGCI '00 Proceedings of the 9th International Conference on Discrete Geometry for Computer Imagery
Steps Toward a Stereo-Camera-Guided Biomechanical Model for Brain Shift Compensation
IPMI '01 Proceedings of the 17th International Conference on Information Processing in Medical Imaging
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Surgical navigation systems are used intraoperatively to provide the surgeon with a display of preoperative and intraoperative data in the same coordinate system and help her or him guide the surgery. However, these systems are subject to inaccuracy caused by intraoperative brain movement (brain shift) since commercial systems in use today typically assume that the intracranial structures are rigid. Experiments show brain shifts up to several millimeters, making it the cause of the dominant error in the system. We propose an image-based brain shift compensation system based on an intraoperatively guided deformable model. We have recorded a set of brain surface points during the surgery and used them to guide and/or validate the model predictions. Initial results show that this system limits the error between its brain surface prediction and real brain surfaces to within 0.5 mm, which is a significant improvement over the systems that are based on the rigid brain assumption, that in this case would have an error of 3 mm or greater.