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 great value in maintaining up-to-date information about changes due to intervention. We propose a mutual information-based registration algorithm which establishes the proper alignment via a stochastic gradient ascent strategy. Our 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. Experimental results are presented on fluoroscopy and CT datasets of a real skull, and on a CT-derived dataset of a real skull, a plastic skull and a plastic lumbar spine segment.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    2D-3D rigid registration of X-ray fluoroscopy and CT images using mutual information and sparsely sampled histogram estimators


    Contributors:
    Zollei, L. (author) / Grimson, E. (author) / Norbash, A. (author) / Wells, W. (author)


    Publication date :

    2001-01-01


    Size :

    1088399 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    2D-3D Rigid Registration of X-Ray Fluoroscopy and CT Images Using Mutual Information and Sparsely Sampled Histogram Estimators

    Zollei, L. / Grimson, E. / Norbash, A. et al. | British Library Conference Proceedings | 2001



    Texture recognition from sparsely and irregularly sampled data

    Petrou, M. / Piroddi, R. / Talebpour, A. | British Library Online Contents | 2006


    Registration of sar images by mutual information

    European Patent Office | 2015

    Free access