Multilevel Non-parametric Groupwise Registration in Cardiac MRI: Application to Explanted Porcine Hearts

  • Mia Mojica
  • Mihaela Pop
  • Maxime Sermesant
  • Mehran Ebrahimi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10663)


Statistical atlases of myocardial fiber directions have great utility in modelling applications. The first step in building atlases requires a registration of the hearts to a template. In this paper, we performed groupwise registration on a small database of explanted pig hearts (\(N=4\)) and coupled it with a multilevel pairwise registration framework in order to generate an average cardiac geometry. The scheme implemented in our experiments effectively registers and normalizes the hearts despite a high variability in cardiac measurements. In addition, we adopted an intuitive averaging technique on the transformed versions of each heart to obtain a new reference geometry at every iteration. This reduces biases that may be introduced by the selection of an initial reference geometry in the construction of an average cardiac geometry. The next step will focus on improving current results by using a larger database of heart samples.


Image registration Inverse problems Cardiac MRI Multilevel registration Non-parametric registration Groupwise registration Cardiac atlas 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of ScienceUniversity of Ontario Institute of TechnologyOshawaCanada
  2. 2.Department of Medical Biophysics, Sunnybrook Research InstituteUniversity of TorontoTorontoCanada
  3. 3.Asclepios Team, INRIASophia AntipolisFrance

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