2D-3D Rigid Registration of X-Ray Fluoroscopy and CT Images Using Mutual Information and Sparsely Sampled Histogram Estimators
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. This paper proposes a mutual information-based registration algorithm which establishes the proper alignment via a stochastic gradient ascent strategy. Its main contribution lies in estimating probability density measures of image intensities with a sparse histogramming method which could lead to potential speedup over existing registration procedures and deriving the gradient estimates required by the maximization procedure.