Variational image registration by a total fractional-order variation model

Jianping Zhang, Ke Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

65 Citations (Scopus)

Abstract

In this paper, a new framework of nonlocal deformation in non-rigid image registration is presented. It is well known that many non-rigid image registration techniques may lead to unsteady deformation (e.g. not one to one) if the dissimilarity between the reference and template images is too large. We present a novel variational framework of the total fractional-order variation to derive the underlying fractional Euler-Lagrange equations and a numerical implementation combining the semi-implicit update and conjugate gradients (CG) solution to solve the nonlinear systems. Numerical experiments show that the new registration not only produces accurate and smooth solutions but also allows for a large rigid alignment, the evaluations of the new model demonstrate substantial improvements in accuracy and robustness over the conventional image registration approaches.

Original languageEnglish
Pages (from-to)442-461
Number of pages20
JournalJournal of Computational Physics
Volume293
Early online date24 Feb 2015
DOIs
Publication statusPublished - 15 Jul 2015

Funding

This work was supported by the UK EPSRC grant (number EP/K036939/1 ) and the National Natural Science Foundation of China (NSFC Project number 11301447 ).

Keywords

  • fractional derivatives
  • image registration
  • inverse problem
  • PDE
  • total fractional-order variation

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