2D-3D Rigid-Body Registration of X-Ray Fluoroscopy and CT Images

The registration of pre-operative volumetric datasets to intra-operative two-dimensional images provides an improved way of verifying patient position and medical instrument location. In applications from orthopedics to neurosurgery, it has a great value in maintaining up-to-date information about changes due to intervention. We propose a mutual information-based registration algorithm to establish the proper alignment. For optimization purposes, we compare the performance of the non-gradient Powell method and two slightly different versions of a stochastic gradient ascent strategy: one using a sparsely sampled histogramming approach and the other Parzen windowing to carry out probability density approximation. Our main contribution lies in adopting the stochastic approximation scheme successfully applied in 3D-3D registration problems to the 2D3D scenario, which obviates the need for the generation of full DRRs at each iteration of pose optimization. This facilitates a considerable savings in computation expense. We also introduce a new probability density estimator for image intensities via sparse histogramming, derive gradient estimates for the density measures required by the maximization procedure and introduce the framework for a multiresolution strategy to the problem. Registration results are presented on fluoroscopy and CT datasets of a plastic pelvis and a real skull, and on a high-resolution CT-derived simulated dataset of a real skull, a plastic skull, a plastic pelvis and a plastic lumbar spine segment. Thesis Supervisor: W. Eric L. Grimson Title: Bernard Gordon Chair of Medical Engineering and Professor of Computer Science and Engineering, MIT AI Lab Thesis Supervisor: William M. Wells III. Title: Research Scientist, MIT AI Lab Assistant Professor of Radiology, Harvard Medical School and Brigham and Womens’ Hospital 2D-3D Rigid-Body Registration of X-Ray Fluoroscopy and CT Images by Lilla Zöllei Submitted to the Department of Electrical Engineering and Computer Science on August 10, 2001, in partial fulfillment of the requirements for the degree of Masters in Electrical Engineering and Computer Science