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Large Deformation Diffeomorphic Metric Curve Mapping

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Abstract

We present a matching criterion for curves and integrate it into the large deformation diffeomorphic metric mapping (LDDMM) scheme for computing an optimal transformation between two curves embedded in Euclidean space ℝd. Curves are first represented as vector-valued measures, which incorporate both location and the first order geometric structure of the curves. Then, a Hilbert space structure is imposed on the measures to build the norm for quantifying the closeness between two curves. We describe a discretized version of this, in which discrete sequences of points along the curve are represented by vector-valued functionals. This gives a convenient and practical way to define a matching functional for curves. We derive and implement the curve matching in the large deformation framework and demonstrate mapping results of curves in ℝ2 and ℝ3. Behaviors of the curve mapping are discussed using 2D curves. The applications to shape classification is shown and experiments with 3D curves extracted from brain cortical surfaces are presented.

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Authors and Affiliations

  1. MAP5, CNRS UMR 8145, Université Paris Descartes, 75006, Paris, France

    Joan Glaunès

  2. Division of Bioengineering, National University of Singapore, 7 Engineering Drive 1, Block E3A 04-15, Singapore, 117574, Singapore

    Anqi Qiu

  3. Center for Imaging Science, Johns Hopkins University, Baltimore, MD, 21218, USA

    Michael I. Miller

  4. Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, 21218, USA

    Laurent Younes

Authors
  1. Joan Glaunès
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  2. Anqi Qiu
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  3. Michael I. Miller
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  4. Laurent Younes
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Corresponding author

Correspondence to Anqi Qiu.

Additional information

J. Glaunès and A. Qiu contributed equally to this work.

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Glaunès, J., Qiu, A., Miller, M.I. et al. Large Deformation Diffeomorphic Metric Curve Mapping. Int J Comput Vis 80, 317–336 (2008). https://doi.org/10.1007/s11263-008-0141-9

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  • DOI: https://doi.org/10.1007/s11263-008-0141-9

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