TY - JOUR
T1 - An intensity consistent filtering approach to the analysis of deformation tensor derived maps of brain shape
AU - Studholme, C.
AU - Cardenas, V.
AU - Maudsley, A.
AU - Weiner, M.
N1 - Funding Information:
This study was primarily funded by the Whitaker Foundation. Image data used in this study was acquired as part of NIH grants P01 AG12435 and R01 AG10897. The authors wish to thank Bruce Miller, Howard Rosen, and Helena Chui for access to data and useful discussions on dementia and aging. We would also like to thank the anonymous reviewing procedure for valuable comments and suggestions that considerably improved the manuscript.
PY - 2003/8/1
Y1 - 2003/8/1
N2 - Deformation tensor morphometry makes use of the derivatives of spatial transformations between anatomies, to provide highly localized volumetric maps of relative anatomical size. The analysis of such maps, however, has the challenge of describing the data in a way that allows the spatial scale and extent of the local shape properties to match those induced by the disease process being studied. This study examines an approach to the spatial filtering of transformation Jacobian maps created in multisubject studies of brain anatomy, which constrains the filter neighborhood within common structural boundaries present in the spatially normalized image data. The filtering incorporates information derived from the spatial normalization process, using a statistical framework to introduce a measure of uncertainty in local regional intensity correspondence following spatial normalisation. The proposed filtering approach is compared to the use of spatially invariant Gaussian filtering in the analysis of Jacobian determinant maps of brain shape and shape change in Alzheimer's disease and normal aging. Results show significantly improved delineation of fine scale patterns of shape difference (in cross-sectional studies) and shape change (from multiple serial magnetic resonance imaging studies).
AB - Deformation tensor morphometry makes use of the derivatives of spatial transformations between anatomies, to provide highly localized volumetric maps of relative anatomical size. The analysis of such maps, however, has the challenge of describing the data in a way that allows the spatial scale and extent of the local shape properties to match those induced by the disease process being studied. This study examines an approach to the spatial filtering of transformation Jacobian maps created in multisubject studies of brain anatomy, which constrains the filter neighborhood within common structural boundaries present in the spatially normalized image data. The filtering incorporates information derived from the spatial normalization process, using a statistical framework to introduce a measure of uncertainty in local regional intensity correspondence following spatial normalisation. The proposed filtering approach is compared to the use of spatially invariant Gaussian filtering in the analysis of Jacobian determinant maps of brain shape and shape change in Alzheimer's disease and normal aging. Results show significantly improved delineation of fine scale patterns of shape difference (in cross-sectional studies) and shape change (from multiple serial magnetic resonance imaging studies).
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U2 - 10.1016/S1053-8119(03)00183-6
DO - 10.1016/S1053-8119(03)00183-6
M3 - Article
C2 - 12948718
AN - SCOPUS:0041422641
VL - 19
SP - 1638
EP - 1649
JO - NeuroImage
JF - NeuroImage
SN - 1053-8119
IS - 4
ER -