Non-parametric Discrete Registration with Convex Optimisation

  • Mattias P. Heinrich
  • Bartlomiej W. Papież
  • Julia A. Schnabel
  • Heinz Handels
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8545)


Deformable image registration is an important step in medical image analysis. It enables an automatic labelling of anatomical structures using atlas-based segmentation, motion compensation and multi-modal fusion. The use of discrete optimisation approaches has recently attracted a lot attention for mainly two reasons. First, they are able to find an approximate global optimum of the registration cost function and can avoid false local optima. Second, they do not require a derivative of the similarity metric, which increases their flexibility. However, the necessary quantisation of the deformation space causes a very large number of degrees of freedom with a high computational complexity. To deal with this, previous work has focussed on parametric transformation models. In this work, we present an efficient non-parametric discrete registration method using a filter-based similarity cost aggregation and a decomposition of similarity and regularisation term into two convex optimisation steps. This approach enables non-parametric registration with billions of degrees of freedom with computation times of less than a minute. We apply our method to two different common medical image registration tasks, intra-patient 4D-CT lung motion estimation and inter-subject MRI brain registration for segmentation propagation. We show improvements on current state-of-the-art performance both in terms of accuracy and computation time.


Image Registration Convex Optimisation Global Regularisation Target Registration Error Cost Aggregation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Mattias P. Heinrich
    • 1
  • Bartlomiej W. Papież
    • 2
  • Julia A. Schnabel
    • 2
  • Heinz Handels
    • 1
  1. 1.Institute of Medical InformaticsUniversity of LübeckGermany
  2. 2.Institute of Biomedical Engineering, Department of EngineeringUniversity of OxfordUK

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