Automatic point landmark matching for regularizing nonlinear intensity registration: Application to thoracic CT images

Martin Urschler*, Christopher Zach, Hendrik Ditt, Horst Bischof

*Korrespondierende/r Autor/in für diese Arbeit

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem Konferenzband

Abstract

Nonlinear image registration is a prerequisite for a variety of medical image analysis tasks. A frequently used registration method is based on manually or automatically derived point landmarks leading to a sparse displacement field which is densified in a thin-plate spline (TPS) framework. A large problem of TPS interpolation/approximation is the requirement for evenly distributed landmark correspondences over the data set which can rarely be guaranteed by landmark matching algorithms. We propose to overcome this problem by combining the sparse correspondences with intensity-based registration in a generic nonlinear registration scheme based on the calculus of variations. Missing landmark information is compensated by a stronger intensity term, thus combining the strengths of both approaches. An explicit formulation of the generic framework is derived that constrains an intra-modality intensity data term with a regularization term from the corresponding landmarks and an anisotropic image-driven displacement regularization term. An evaluation of this algorithm is performed comparing it to an intensity- and a landmark-based method. Results on four synthetically deformed and four clinical thorax CT data sets at different breathing states are shown. © Springer-Verlag Berlin Heidelberg 2006.

Originalspracheenglisch
TitelMedical Image Computing and Computer-Assisted Intervention – MICCAI 2006
Untertitel9th International Conference, Copenhagen, Denmark, October 1-6, 2006. Proceedings, Part II
Redakteure/-innenRasmus Larsen, Mads Nielsen, Jon Sporring
ErscheinungsortBerlin Heidelberg
Herausgeber (Verlag)Springer
Seiten710-717
Seitenumfang8
Band4191
ISBN (elektronisch)978-3-540-44728-3
ISBN (Print)978-3-540-44727-6
DOIs
PublikationsstatusVeröffentlicht - 2006
Veranstaltung9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - Copenhagen, Dänemark
Dauer: 1 Okt 20066 Okt 2006

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band4191 LNCS - II
ISSN (Print)03029743
ISSN (elektronisch)16113349

Konferenz

Konferenz9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006
LandDänemark
OrtCopenhagen
Zeitraum1/10/066/10/06

Fields of Expertise

  • Information, Communication & Computing

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  • Projekte

    • 1 Abschlussdatum

    Nonlinear Registration for Intra-Modality Registration of Medical Volume Data

    Urschler, M. & Bischof, H.

    1/06/0430/05/07

    Projekt: Foschungsprojekt

    Dieses zitieren

    Urschler, M., Zach, C., Ditt, H., & Bischof, H. (2006). Automatic point landmark matching for regularizing nonlinear intensity registration: Application to thoracic CT images. in R. Larsen, M. Nielsen, & J. Sporring (Hrsg.), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006: 9th International Conference, Copenhagen, Denmark, October 1-6, 2006. Proceedings, Part II (Band 4191, S. 710-717). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 4191 LNCS - II). Berlin Heidelberg: Springer. https://doi.org/10.1007/11866763_87