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PMID: 20211269 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.

Tensor-based morphometry with stationary velocity field diffeomorphic registration: application to ADNI.

NeuroImage ·Vol. 51 ·No. 3 ·2010-07-01 ·Pages 956-69

Bossa M, Zacur E, Olmos S, Alzheimer's Disease Neuroimaging Initiative

Abstract

Tensor-based morphometry (TBM) is an analysis technique where anatomical information is characterized by means of the spatial transformations mapping a customized template with the observed images. Therefore, accurate inter-subject non-rigid registration is an essential prerequisite for both template estimation and image warping. Subsequent statistical analysis on the spatial transformations is performed to highlight voxel-wise differences. Most of previous TBM studies did not explore the influence of the registration parameters, such as the parameters defining the deformation and the regularization models. In this work performance evaluation of TBM using stationary velocity field (SVF) diffeomorphic registration was performed in a subset of subjects from Alzheimer's Disease Neuroimaging Initiative (ADNI) study. A wide range of values of the registration parameters that define the transformation smoothness and the balance between image matching and regularization were explored in the evaluation. The proposed methodology provided brain atrophy maps with very detailed anatomical resolution and with a high significance level compared with results recently published on the same data set using a non-linear elastic registration method.

MeSH Terms
Aged Aged, 80 and over Algorithms Alzheimer Disease/pathology Brain/pathology Diffusion Magnetic Resonance Imaging/methods Female Humans Image Enhancement/methods Image Interpretation, Computer-Assisted/methods Imaging, Three-Dimensional/methods Male Middle Aged Reproducibility of Results Sensitivity and Specificity Subtraction Technique
Authors & Affiliations
4 authors, click to expand affiliations / ORCID
Bossa Matias
GTC, Aragon Institute of Engineering Research, Universidad de Zaragoza, Spain.
Zacur Ernesto
Olmos Salvador
Alzheimer's Disease Neuroimaging Initiative
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Article Info
Journal
NeuroImage
Abbr.
Neuroimage
ISSN
1095-9572
DOI
10.1016/j.neuroimage.2010.02.061
Published
2010-07-01
Epub
2010-00-06
Pages
956-69
Language
English
Region
United States
NLM ID
9215515
PMCID
PMC3068621
Subset
IM
Grants
NIA NIH HHS · U01 AG024904 · United States
NIA NIH HHS · U01 AG024904-01 · United States
NIA NIH HHS · U19 AG010483 · United States
External Links
PubMed source DOI: 10.1016/j.neuroimage.2010.02.061 PMC Full Text View journal details
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