Multi-modality image registration using the decomposition model

Mazlinda Ibrahim*, Ke Chen

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

In medical image analysis, image registration is one of the crucial steps required to facilitate automatic segmentation, treatment planning and other application involving imaging machines. Image registration, also known as image matching, aims to align two or more images so that information obtained can be compared and combined. Different imaging modalities and their characteristics make the task more challenging. We propose a decomposition model combining parametric and non-parametric deformation for multi-modality image registration. Numerical results show that the normalised gradient field perform better than the mutual information with the decomposition model.

Original languageEnglish
Article number020007
JournalAIP Conference Proceedings
Volume1830
Issue number1
DOIs
Publication statusPublished - 27 Apr 2017
Event4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016 - Putrajaya, Malaysia
Duration: 15 Nov 201617 Nov 2016

Keywords

  • image matching
  • decomposition model

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