Improved correspondence for DTI population studies via unbiased atlas building

Casey Goodlett, Brad Davis, Remi Jean, John Gilmore, Guido Gerig

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    We present a method for automatically finding correspondence in Diffusion Tensor Imaging (DTI) from deformable registration to a common atlas. The registration jointly produces an average DTI atlas, which is unbiased with respect to the choice of a template image, along with diffeomorphic correspondence between each image. The registration image match metric uses a feature detector for thin fiber structures of white matter, and interpolation and averaging of diffusion tensors use the Riemannian symmetric space framework. The anatomically significant correspondence provides a basis for comparison of tensor features and fiber tract geometry in clinical studies and for building DTI population atlases.

    Original languageEnglish (US)
    Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings
    Pages260-267
    Number of pages8
    Volume4191 LNCS - II
    StatePublished - 2006
    Event9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - Copenhagen, Denmark
    Duration: Oct 1 2006Oct 6 2006

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume4191 LNCS - II
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006
    CountryDenmark
    CityCopenhagen
    Period10/1/0610/6/06

    Fingerprint

    Diffusion tensor imaging
    Diffusion Tensor Imaging
    Atlases
    Atlas
    Correspondence
    Tensor
    Imaging
    Tensors
    Population
    Fibers
    Image registration
    Registration
    Fiber
    Interpolation
    Riemannian Symmetric Space
    Detectors
    Image Registration
    Geometry
    Averaging
    Template

    ASJC Scopus subject areas

    • Computer Science(all)
    • Biochemistry, Genetics and Molecular Biology(all)
    • Theoretical Computer Science

    Cite this

    Goodlett, C., Davis, B., Jean, R., Gilmore, J., & Gerig, G. (2006). Improved correspondence for DTI population studies via unbiased atlas building. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings (Vol. 4191 LNCS - II, pp. 260-267). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4191 LNCS - II).

    Improved correspondence for DTI population studies via unbiased atlas building. / Goodlett, Casey; Davis, Brad; Jean, Remi; Gilmore, John; Gerig, Guido.

    Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings. Vol. 4191 LNCS - II 2006. p. 260-267 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4191 LNCS - II).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Goodlett, C, Davis, B, Jean, R, Gilmore, J & Gerig, G 2006, Improved correspondence for DTI population studies via unbiased atlas building. in Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings. vol. 4191 LNCS - II, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4191 LNCS - II, pp. 260-267, 9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006, Copenhagen, Denmark, 10/1/06.
    Goodlett C, Davis B, Jean R, Gilmore J, Gerig G. Improved correspondence for DTI population studies via unbiased atlas building. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings. Vol. 4191 LNCS - II. 2006. p. 260-267. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
    Goodlett, Casey ; Davis, Brad ; Jean, Remi ; Gilmore, John ; Gerig, Guido. / Improved correspondence for DTI population studies via unbiased atlas building. Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings. Vol. 4191 LNCS - II 2006. pp. 260-267 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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