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Titolo:
Enhancing the multivariate signal of [O-15] water PET studies with a new nonlinear neuroanatomical registration algorithm
Autore:
Kjems, U; Strother, SC; Anderson, J; Law, I; Hansen, LK;
Indirizzi:
Tech Univ Denmark, Dept Math Modeling, DK-2800 Lyngby, Denmark Tech Univ Denmark Lyngby Denmark DK-2800 deling, DK-2800 Lyngby, Denmark VA Med Ctr, PET Imaging Serv, Minneapolis, MN USA VA Med Ctr Minneapolis MN USA Ctr, PET Imaging Serv, Minneapolis, MN USA Univ Minnesota, Dept Radiol, Minneapolis, MN 55455 USA Univ Minnesota Minneapolis MN USA 55455 Radiol, Minneapolis, MN 55455 USA Univ Minnesota, Dept Neurol, Minneapolis, MN 55455 USA Univ Minnesota Minneapolis MN USA 55455 Neurol, Minneapolis, MN 55455 USA Univ Minnesota, Dept Hlth Informat, Minneapolis, MN 55455 USA Univ Minnesota Minneapolis MN USA 55455 format, Minneapolis, MN 55455 USA Natl Univ Hosp, Dept Neurol, Copenhagen, Denmark Natl Univ Hosp Copenhagen Denmark osp, Dept Neurol, Copenhagen, Denmark
Titolo Testata:
IEEE TRANSACTIONS ON MEDICAL IMAGING
fascicolo: 4, volume: 18, anno: 1999,
pagine: 306 - 319
SICI:
0278-0062(199904)18:4<306:ETMSO[>2.0.ZU;2-A
Fonte:
ISI
Lingua:
ENG
Soggetto:
AUTOMATED IMAGE REGISTRATION; SCALED SUBPROFILE MODEL; LINEAR-MODELS; BRAIN IMAGES; MR-IMAGES; NORMALIZATION; ACTIVATION; VALIDATION;
Keywords:
intersubject registration; nonlinear warping; stereotactic registration; voxel similarity measures;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Clinical Medicine
Engineering, Computing & Technology
Citazioni:
50
Recensione:
Indirizzi per estratti:
Indirizzo: Kjems, U Tech Univ Denmark, Dept Math Modeling, DK-2800 Lyngby, Denmark Tech Univ Denmark Lyngby Denmark DK-2800 K-2800 Lyngby, Denmark
Citazione:
U. Kjems et al., "Enhancing the multivariate signal of [O-15] water PET studies with a new nonlinear neuroanatomical registration algorithm", IEEE MED IM, 18(4), 1999, pp. 306-319

Abstract

This paper addresses the problem of neuro-anatomical registration across individuals for functional [O-15] water PET activation studies. A nem algorithm for three-dimensional (3-D) nonlinear structural registration ( warping) of MR scans is presented. The method performs a hierarchically scaled search for a displacement field, maximizing one of several voxel similarity measures derived from the two-dimensional (2-D) histogram of matched image intensities, subject to a regularizer that ensures smoothness of the displacement field. The effect of the nonlinear structural registration is studied when it is computed on anatomical MR scans and applied to coregistered [O-15] water PET scans from the same subjects: in this experiment, a study of visually guided saccadic eye movements. The performance of the nonlinear warp is evaluated using multivariate functional signal and noise measures. These measures prove to be useful for comparing different intersubject registration approaches, e,g., affine versus nonlinear,A comparison of 12-parameter affine registration versus nonlinear registration demonstrates that the proposed nonlinear method increases the number of voxels retained in the cross-subject mask. We demonstrate that improved structural registration may result in an improved multivariate functional signal-to-noise ratio (SNR). Furthermore, registration of PET scans using the12-parameter affine transformations that align the coregistered MR images does not improve registration, compared to 12-parameter affine alignment ofthe PET images directly.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 06/04/20 alle ore 05:45:21