Effect of nonrigid registration algorithms on deformation-based morphometry: a comparative study with control and Williams syndrome subjects

Deformation-based morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of the deformation fields generated by nonrigid registration algorithms, which warp the individual volumes to a DBM atlas. Although several studies have c...

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Bibliographic Details
Published in:Magnetic resonance imaging Vol. 30; no. 6; pp. 774 - 788
Main Authors: Han, Zhaoying, Thornton-Wells, Tricia A., Dykens, Elisabeth M., Gore, John C., Dawant, Benoit M.
Format: Journal Article
Language:English
Published: Netherlands Elsevier Inc 01.07.2012
Subjects:
Adult
Algorithms
Brain - pathology
Brain atlas
Deformation-based morphometry
Female
Humans
Image processing
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Male
Mapping
Morphometry
Nonrigid registration
Radiology
Segmentation
Statistics
Williams syndrome
Williams Syndrome - pathology
Young Adult
Deformation-based morphometry
Brain atlas
Nonrigid registration
Williams syndrome
ISSN:0730-725X, 1873-5894, 1873-5894
Online Access:Get full text
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Summary:Deformation-based morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of the deformation fields generated by nonrigid registration algorithms, which warp the individual volumes to a DBM atlas. Although several studies have compared nonrigid registration algorithms for segmentation tasks, few studies have compared the effect of the registration algorithms on group differences that may be uncovered through DBM. In this study, we compared group atlas creation and DBM results obtained with five well-established nonrigid registration algorithms using 13 subjects with Williams syndrome and 13 normal control subjects. The five nonrigid registration algorithms include the following: (1) the adaptive bases algorithm, (2) the image registration toolkit, (3) The FSL nonlinear image registration tool, (4) the automatic registration tool, and (5) the normalization algorithm available in Statistical Parametric Mapping (SPM8). Results indicate that the choice of algorithm has little effect on the creation of group atlases. However, regions of differences between groups detected with DBM vary from algorithm to algorithm both qualitatively and quantitatively. Some regions are detected by several algorithms, but their extent varies. Others are detected only by a subset of the algorithms. Based on these results, we recommend using more than one algorithm when performing DBM studies.
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ISSN:0730-725X
1873-5894
1873-5894
DOI:10.1016/j.mri.2012.02.005