Spatial transformations of diffusion tensor magnetic resonance images

By Daniel C. Alexander, Carlo Pierpaoli, Peter J. Basser, James C. Gee. IEEE Transactions on Medical Imaging, 2001

657 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/a88c3829ecd4040dd89bc685ac7e594920c8c1e5

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In Computer Vision and Pattern Recognition

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Citations in the corpus

Cognitive processing speed and the structure of white matter pathways: Convergent evidence from normal variation and lesion studies (2008, neutral): “Images were averaged across repetitions prior to normalization, and gradient vectors were reoriented to adjust for the rotational component of the normalization transformation (Alexander et al., 2001).”
Occipito-temporal connections in the human brain. (2003, methodology): “Each of the remaining 10 subject's data sets was coregistered (using an af®ne registration with 12 degrees of freedom) to the target fractional anisotropy volume using the approach described by Alexander et al. (2001).”
Characterizing brain anatomical connections using diffusion weighted MRI and graph theory (2007, methodology): “Tensors were rotated according to the method presented by Alexander and coworkers (Alexander et al., 2001).”
Atlas-based whole brain white matter analysis using large deformation diffeomorphic metric mapping: Application to normal elderly and Alzheimer’s disease participants (2009, positive): “In this study, we used Gee and Alexander's method (Alexander et al., 2001; Xu et al., 2003), which is one of the simplest and, currently, most widely used methods.”
Fast parallel image registration on CPU and GPU for diagnostic classification of Alzheimer's disease (2013, neutral): “…development, alignment of different MR sequences for extraction of quantitative MR parameters such as in diffusion tensor imaging or MR relaxometry (Alexander et al., 2001; Bron et al., 2013), alignment of pre-and post-contrast images (Rueckert et al., 1999) to aid breast cancer detection and…”
The NIH MRI study of normal brain development (2006, positive): “Tensor re-orientation strategies (Alexander et al., 2001) were used to resample tensor quantities in stereotaxic space.”
About “axial” and “radial” diffusivities (2009, methodology): “The transformations were then applied to each component of the DT using the PPD (preservation of principal direction) algorithm (20).”
Differences in White Matter Fiber Tract Development Present from 6 to 24 Months in Infants with Autism (2012, methodology): “Tensor maps were calculated from each DWI dataset using weighted least squares estimation, and transformed into the atlas space with tensor re-orientation by a finite strain approach (44).”
Perisylvian language networks of the human brain (2005, neutral): “Spatial normalization of tensor volumes is more complicated than that for scalar volumes (eg, T1-weighted intensity maps), because the orientations of the tensor must be correctly preserved.(24) Once normalized, a mean of 10 diffusion tensors in each voxel was computed to produce a mean diffusion te”
Automatic mapping of atrial fiber orientations for patient‐specific modeling of cardiac electromechanics using image registration (2018, neutral): “To reorient the fiber directions, two strategies are possible, the finite strain strategy and the strategy of principal directions [30].”
Investigating white matter fibre density and morphology using fixel-based analysis (2017, background): “(4) from Alexander et al. (2001): ^′ = ^ ^ ( ) v Jv Jv 1 f f f where v̂f is the unit vector describing the original direction of the fixel, ^′v f is the reoriented direction, and J is the Jacobian matrix that describes the local affine transformation of the non-linear warp, defined as: ⎡ ⎣ ⎢ ⎢ ⎢ ⎢…”
Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template (2008, methodology): “The transformation matrix was then applied to the calculated diffusion tensor field, based on the method described by Alexander et al. (2001) and Xu et al. (2003).”
Human Brain White Matter Atlas: Identification and Assignment of Common Anatomical Structures in Superficial White Matter (2008, methodology): “The transformation matrix was then applied to the calculated diffusion tensor field, based on the method described by Alexander and Gee (Alexander et al., 2001) and Xu et al. (Xu et al., 2003).”