Deformation invariant attribute vector for deformable registration of longitudinal brain MR images

Gang Li, Lei Guo, Tianming Liu

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This paper presents a novel approach to define deformation invariant attribute vector (DIAV) for each voxel in 3D brain image for the purpose of anatomic correspondence detection. The DIAV method is validated by using synthesized deformation in 3D brain MRI images. Both theoretic analysis and experimental studies demonstrate that the proposed DIAV is invariant to general nonlinear deformation. Moreover, our experimental results show that the DIAV is able to capture rich anatomic information around the voxels and exhibit strong discriminative ability. The DIAV has been integrated into a deformable registration algorithm for longitudinal brain MR images, and the results on both simulated and real brain images are provided to demonstrate the good performance of the proposed registration algorithm based on matching of DIAVs.

Original languageEnglish
Pages (from-to)384-398
Number of pages15
JournalComputerized Medical Imaging and Graphics
Volume33
Issue number5
DOIs
StatePublished - Jul 2009

Keywords

  • Brain MRI
  • Deformable registration
  • Deformation invariant attribute vector
  • Longitudinal imaging

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