An iterative framework for improving the accuracy of intraoperative intensity-based 2D/3D registration for image-guided orthopedic surgery

Authors:
Yoshito Otake;Mehran Armand;Ofri Sadowsky;Robert S. Armiger;Peter Kazanzides;Russell H. Taylor
Affiliations:
Department of Computer Science, The Johns Hopkins University, Baltimore, MD;The Johns Hopkins University, Applied Physics Laboratory, Laurel, Maryland;Department of Computer Science, Johns Hopkins University, Baltimore, MD;The Johns Hopkins University, Applied Physics Laboratory, Laurel, Maryland;Department of Computer Science, Johns Hopkins University, Baltimore, MD;Department of Computer Science, Johns Hopkins University, Baltimore, MD
Venue:
IPCAI'10 Proceedings of the First international conference on Information processing in computer-assisted interventions
Year:
2010

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Abstract

We propose an iterative refinement framework that improves the accuracy of intraoperative intensity-based 2D/3D registration. The method optimizes both the extrinsic camera parameters and the object pose. The algorithm estimates the transformation between the fiducials and the patient intraoperatively using a small number of X-ray images. The proposed algorithm was validated in an experiment using a cadaveric phantom, in which the true registration was acquired from CT data. The results of 50 registration trials with randomized initial conditions on a pair of X-ray C-arm images taken at 32° angular separation showed that the iterative refinement process improved the translational error by 0.32 mm and the rotational error by 0.61 degrees when compared to the 2D/3D registration without iteration. This tool has the potential to allow routine use of image guided therapy by computing registration parameters using only two X-ray images.