@CONFERENCE\{IMM1997-0241,
    author       = "M. Bro-Nielsen",
    title        = "Rigid registration of {CT,} {MR} and cryosection images using a {GLCM} framework",
    year         = "1997",
    keywords     = "biomedical {NMR}; computerised tomography; image registration; image texture; matrix algebra; medical image processing",
    pages        = "171-180",
    booktitle    = "CVRMed{-MRCAS} '97. 1st Joint Conf, Comp Vision, {VR} and Robotics in Medicine and Medical Robotics and Comp-Assisted Surgery Proc",
    volume       = "1205",
    series       = "Lecture Notes in Computer Science",
    editor       = "Troccaz, J.;  Grimson, E.;  Mosges, R.",
    publisher    = "Springer-Verlag",
    organization = "",
    address      = "",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/241-full.html",
    abstract     = "The majority of the available rigid registration measures are based on a {2-}dimensional histogram of corresponding grey-values in the registered images. This paper shows that these features are similar to a family of texture measures based on grey level co-occurrence matrices (GLCM). Features from the {GLCM} literature are compared to the current range of measures using images from the visible human data set. The voxel-based rigid registration of cryosection and {CT} images have not been reported before. The tests show that mutual information is the best general measure, but some {GLCM} features are better for specific modality combinations. This paper discusses existing and some new voxel similarity measures for image registration. Elaborate tests are used to evaluate the different measures and compare them. Finally, a registration algorithm based on voxel similarity measures is described and some results are presented",
    isbn_issn    = "3540627340"
}