Simultaneous multiscale polyaffine registration by incorporating deformation statistics

Christof Seiler, Xavier Pennec, Mauricio Reyes

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review


Locally affine (polyaffine) image registration methods capture intersubject non-linear deformations with a low number of parameters, while providing an intuitive interpretation for clinicians. Considering the mandible bone, anatomical shape differences can be found at different scales, e.g. left or right side, teeth, etc. Classically, sequential coarse to fine registration are used to handle multiscale deformations, instead we propose a simultaneous optimization of all scales. To avoid local minima we incorporate a prior on the polyaffine transformations. This kind of groupwise registration approach is natural in a polyaffine context, if we assume one configuration of regions that describes an entire group of images, with varying transformations for each region. In this paper, we reformulate polyaffine deformations in a generative statistical model, which enables us to incorporate deformation statistics as a prior in a Bayesian setting. We find optimal transformations by optimizing the maximum a posteriori probability. We assume that the polyaffine transformations follow a normal distribution with mean and concentration matrix. Parameters of the prior are estimated from an initial coarse to fine registration. Knowing the region structure, we develop a blockwise pseudoinverse to obtain the concentration matrix. To our knowledge, we are the first to introduce simultaneous multiscale optimization through groupwise polyaffine registration. We show results on 42 mandible CT images.

Original languageEnglish
Title of host publicationInternational Conference on Medical Image Computing and Computer-Assisted Intervention
Number of pages8
EditionPt 2
Publication statusPublished - 2012
Externally publishedYes

Publication series

SeriesMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention


  • Algorithms
  • Data Interpretation, Statistical
  • Humans
  • Image Enhancement/methods
  • Image Interpretation, Computer-Assisted/methods
  • Mandible/diagnostic imaging
  • Pattern Recognition, Automated/methods
  • Radiography, Dental/methods
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Subtraction Technique

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