"Voxel-Based Morphometry" Should Not Be Used with Imperfectly Registered Images

By Fred L. Bookstein. NeuroImage, 2001

687 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Geometry and Topology, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/164a08ebcf6d3db886f8efd751567117d32b25d9

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Citations in the corpus

The neuroanatomy of general intelligence: sex matters (2005, methodology): “VBM and ROI methods have their respective strengths and weaknesses (Ashburner and Friston, 2001; Bookstein, 2001; Davatzikos, 2004; Friston and Ashburner, 2004).”
Aging, training, and the brain: A review and future directions (2009, neutral): “Most studies of training and structural change use of voxel-based morphometry, which has been criticized for potentially distorting estimates of atrophy, errors in classification of white and grey matter, and image registration problems (Ashburner and Friston 2001; Bookstein 2001; Karas et al. 200”
The effect of filter size on VBM analyses of DT-MRI data (2005, neutral): “The interested reader is referred elsewhere for such discussions Ashburner and Friston, 2001; Bookstein, 2001; Crum et al., 2003; Davatzikos, 2004; Salmond et al., 2002).”
Voxel-Based Morphometric Analysis of Gray Matter in First Episode Schizophrenia (2002, background): “…to some systematical biases, which could arise from not only the errors caused by the misregistration of anatomical structures, but also movement or gray and white matter intensity patterns that differ between groups (see Bookstein, 2001, and Ashburner and Friston, 2001, discussion in NeuroImage).”
Dynamics of Gray Matter Loss in Alzheimer's Disease (2003, methodology): “phometry discussed previously in the literature (Ashburner and Friston, 2001; Bookstein, 2001).”
A framework to study the cortical folding patterns. (2004, methodology): “Spatial normalization is currently a popular method for comparing brain images (Brett et al., 2002; Collins et al., 1994; Fischl et al., 1999; Fox et al., 1985; Friston et al., 1995).”
Automatic construction of 3-D statistical deformation models of the brain using nonrigid registration (2003, methodology): “Current morphometric methods can be classified into voxel-based [43], [44] or deformation-based methods [45], [46].”
Global and local gray matter loss in mild cognitive impairment and Alzheimer's disease (2004, background): “Because there has been debate about misregistration influencing the results of VBM (Ashburner and Friston, 2001; Bookstein, 2001) and one of the assumptions for a correct VBM is reduced global anatomical variability (Ashburner and Friston, 2000), we enhanced the averaging process at the…”
Geodesic Information Flows: Spatially-Variant Graphs and Their Application to Segmentation and Fusion (2015, background): “Bottom) The information ﬂows only between the neighbours of the target subject. a problem which has generated wide criticism [4], [5]; and (3) groupwise spaces confound the two sources of morphological variation by averaging natural variability (e.g. sulcal patterns, brain shape) and pathological…”
Structural Abnormalities in the Brains of Human Subjects Who Use Methamphetamine (2004, background): “One important question is whether these apparent gains in white - matter volumes might be attributable to MRI signal or volume changes in the adjacent cortical gray matter ( Bookstein , 2001 ) .”
Diffusion tensor imaging with tract-based spatial statistics reveals local white matter abnormalities in preterm infants (2007, positive): “…do not always replicate ROI analyses of DTI data, and given that the choice of spatial smoothing extent of the segmentation output data also remains unresolved, some investigators have concluded that VBM should not be used with imperfectly registered images (Bookstein, 2001; Davatzikos, 2004).”
The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence (2007, methodology): “As commented in the target article, there has been some dispute over the application of VBM, especially to characterizing group differences (Bookstein 2001; Davatzikos 2004; Mehta et al. 2003).”
Non-rigid image registration: theory and practice. (2004, background): “At the time of writing, it is only in brain applications that non-rigid registration is used on a routine basis even though there remain some questions about its veracity [27, 96–98].”
A comprehensive study of gray matter loss in patients with Alzheimer's disease using optimized voxel-based morphometry (2003, background): “As a result, controls will match the standard template better than AD patients; especially near strong intensity gradients, one runs the danger of measuring structure displacement on top of atrophy (Bookstein, 2001); hence the need for a study-specific template.”