An efficient numerical method for mean curvature-based image registration model

Zhang, Jin and Chen, Ke and Chen, Fang and Yu, Bo (2017) An efficient numerical method for mean curvature-based image registration model. East Asian Journal on Applied Mathematics, 7 (1). pp. 125-142. ISSN 2079-7370 (https://doi.org/10.4208/eajam.200816.031216a)

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Abstract

Mean curvature-based image registration model firstly proposed by Chumchob-Chen-Brito (2011) offered a better regularizer technique for both smooth and nonsmooth deformation fields. However, it is extremely challenging to solve efficiently this model and the existing methods are slow or become efficient only with strong assumptions on the smoothing parameter β. In this paper, we take a different solution approach. Firstly, we discretize the joint energy functional, following an idea of relaxed fixed point is implemented and combine with Gauss-Newton scheme with Armijo's Linear Search for solving the discretized mean curvature model and further to combine with a multilevel method to achieve fast convergence. Numerical experiments not only confirm that our proposed method is efficient and stable, but also it can give more satisfying registration results according to image quality.

ORCID iDs

Zhang, Jin, Chen, Ke ORCID logoORCID: https://orcid.org/0000-0002-6093-6623, Chen, Fang and Yu, Bo;
  • Item type:Article
    ID code:87422
    Dates:
    Date
    Event
    28 February 2017
    Published
    31 January 2017
    Published Online
    3 December 2016
    Accepted
    20 August 2016
    Submitted
    Subjects:Science > Mathematics
    Department:UNSPECIFIED
    Depositing user: Pure Administrator
    Date deposited:22 Nov 2023 16:05
    Last modified:11 Nov 2024 14:09
    URI:https://strathprints.strath.ac.uk/id/eprint/87422
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