2004
DOI: 10.1016/j.media.2004.06.009
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Abstract: Spatial normalization is a key process in cross-sectional studies of brain structure and function using MRI, fMRI, PET and other imaging techniques. A wide range of 2D surface and 3D image deformation algorithms have been developed, all of which involve design choices that are subject to debate. Moreover, most have numerical parameters whose value must be specified by the user. This paper proposes a principled method for evaluating design choices and choosing parameter values. This method can also be used to c… Show more

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Cited by 202 publications
(71 citation statements)
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“…Cortical thickness was defined using the t-link method, which captures the Euclidean distance between linked vertices [39, 56]. Each individual thickness map was transformed to a surface group template using a two-dimensional (2D) surface-based registration [37] and the mean cortical thickness of 39 regions using a surface-based automated anatomical labeling (AAL) template [57]. …”
Section: Methodsmentioning
confidence: 99%
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“…Cortical thickness was defined using the t-link method, which captures the Euclidean distance between linked vertices [39, 56]. Each individual thickness map was transformed to a surface group template using a two-dimensional (2D) surface-based registration [37] and the mean cortical thickness of 39 regions using a surface-based automated anatomical labeling (AAL) template [57]. …”
Section: Methodsmentioning
confidence: 99%
“…The partial volume corrected sFDG (csFDG) was obtained by dividing sFDG by swPVE after diffusion smoothing with a 20 mm FWHM filter. Each csFDG was transformed to the surface template utilizing sphere-to-sphere warping surface registration and 39 regional uptake values were obtained using the AAL template [37, 57]. …”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Cortical thickness was measured in native-space millimeters using the linked distance between the white and pial surfaces at 40,962 vertices throughout the cortex [25]. The subjectwise thickness measurements were nonlinearly aligned to the standard template using two-dimensional (2D) surface registration [26].…”
Section: Subjects Mri Acquisition and Image Processingmentioning
confidence: 99%
“…by removing, to the extent possible, the natural anatomical variability in a population by deforming each individual's anatomy into a standardized space. 35 …”
Section: Introductionmentioning
confidence: 99%