A method to map errors in the deformable registration of 4DCT images

Constantin Vaman, David Staub, Jeffrey Williamson, Martin J. Murphy

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Purpose: To present a new approach to the problem of estimating errors in deformable image registration (DIR) applied to sequential phases of a 4DCT data set. Methods: A set of displacement vector fields (DVFs) are made by registering a sequence of 4DCT phases. The DVFs are assumed to display anatomical movement, with the addition of errors due to the imaging and registration processes. The positions of physical landmarks in each CT phase are measured as ground truth for the physical movement in the DVF. Principal component analysis of the DVFs and the landmarks is used to identify and separate the eigenmodes of physical movement from the error eigenmodes. By subtracting the physical modes from the principal components of the DVFs, the registration errors are exposed and reconstructed as DIR error maps. The method is demonstrated via a simple numerical model of 4DCT DVFs that combines breathing movement with simulated maps of spatially correlated DIR errors. Results: The principal components of the simulated DVFs were observed to share the basic properties of principal components for actual 4DCT data. The simulated error maps were accurately recovered by the estimation method. Conclusions: Deformable image registration errors can have complex spatial distributions. Consequently, point-by-point landmark validation can give unrepresentative results that do not accurately reflect the registration uncertainties away from the landmarks. The authors are developing a method for mapping the complete spatial distribution of DIR errors using only a small number of ground truth validation landmarks.

Original languageEnglish
Pages (from-to)5765-5776
Number of pages12
JournalMedical physics
Volume37
Issue number11
DOIs
StatePublished - Nov 2010

Keywords

  • 4DCT
  • breathing motion
  • deformable image registration
  • principal components analysis
  • registration validation

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