Preliminary study of a novel method for conveying corrected image volumes in surgical navigation

Commercial image‐guided surgery systems rely on the fundamental assumption that preoperative medical images represent the physical state of the patient in the operating room. The guidance display typically consists of a three‐dimensional (3D) model derived from medical images and three orthogonal views of the imaging data. A challenging question in image‐guided surgery is: what happens when the images used in the guidance display no longer correspond to the current geometric state of the anatomy and guidance information is still desirable?

[1]  Simon K Warfield,et al.  3D XFEM-based modeling of retraction for preoperative image update , 2011, Computer aided surgery : official journal of the International Society for Computer Aided Surgery.

[2]  Logan W. Clements,et al.  Robust surface registration using salient anatomical features for image-guided liver surgery: algorithm and validation. , 2008, Medical physics.

[3]  Logan W. Clements,et al.  Concepts and Preliminary Data Toward the Realization of Image-guided Liver Surgery , 2007, Journal of Gastrointestinal Surgery.

[4]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Keith D. Paulsen,et al.  A three-dimensional mesh generator for arbitrary multiple material domains , 1997 .

[6]  Keith D. Paulsen,et al.  In vivo quantification of a homogeneous brain deformation model for updating preoperative images during surgery , 2000, IEEE Transactions on Biomedical Engineering.

[7]  T. Peters,et al.  Overview and History of Image-Guided Interventions , 2008 .

[8]  Keith D. Paulsen,et al.  Model-updated image guidance: initial clinical experiences with gravity-induced brain deformation , 1999, IEEE Transactions on Medical Imaging.

[9]  Robert L. Galloway,et al.  Compensating for intraoperative soft-tissue deformations using incomplete surface data and finite elements , 2005, IEEE Transactions on Medical Imaging.

[10]  B. Dawant,et al.  Liver segmentation in living liver transplant donors: comparison of semiautomatic and manual methods. , 2005, Radiology.

[11]  Michael I. Miga,et al.  The sparse data extrapolation problem: strategies for soft-tissue correction for image-guided liver surgery , 2011, Medical Imaging.

[12]  K. McMasters,et al.  Intraoperative magnetic resonance imaging for ablation of hepatic tumors , 2006, Surgical Endoscopy And Other Interventional Techniques.

[13]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[14]  Keith D. Paulsen,et al.  Displacement estimation with co-registered ultrasound for image guided neurosurgery: a quantitative in vivo porcine study , 2003, IEEE Transactions on Medical Imaging.

[15]  Chengjun Yao,et al.  A Sparse Intraoperative Data-Driven Biomechanical Model to Compensate for Brain Shift during Neuronavigation , 2011, American Journal of Neuroradiology.

[16]  P M Schlag,et al.  Development and validation of a three dimensional ultrasound based navigation system for tumor resection. , 2008, European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology.

[17]  W. Tryon Evaluating statistical difference, equivalence, and indeterminacy using inferential confidence intervals: an integrated alternative method of conducting null hypothesis statistical tests. , 2001, Psychological methods.

[18]  Logan W. Clements,et al.  Model-updated image-guided liver surgery: preliminary results using surface characterization. , 2010, Progress in Biophysics and Molecular Biology.

[19]  P M Schlag,et al.  Image‐guided surgery of liver metastases by three‐dimensional ultrasound‐based optoelectronic navigation , 2007, The British journal of surgery.

[20]  Terry M. Peters,et al.  An integrated range-sensing, segmentation and registration framework for the characterization of intra-surgical brain deformations in image-guided surgery , 2003, Comput. Vis. Image Underst..

[21]  Heinz-Otto Peitgen,et al.  Assessment of Intraoperative Liver Deformation During Hepatic Resection: Prospective Clinical Study , 2010, World Journal of Surgery.

[22]  K. Paulsen,et al.  Modeling of Retraction and Resection for Intraoperative Updating of Images , 2001, Neurosurgery.

[23]  Ron Kikinis,et al.  Serial registration of intraoperative MR images of the brain , 2002, Medical Image Anal..