dti (version 1.4.3.1)

dti-package: dti

Description

dti

Details

The DESCRIPTION file: dti dti

References

S. Mohammadi, K. Tabelow, L. Ruthotto, Th. Feiweier, J. Polzehl, and N. Weiskopf, High-resolution diffusion kurtosis imaging at 3T enabled by advanced post-processing, 8 (2015), 427.

S. Becker, K. Tabelow, S. Mohammadi, N. Weiskopf, and J. Polzehl, Adaptive smoothing of multi-shell diffusion weighted magnetic resonance data by msPOAS, NeuroImage 95 (2014), pp. 90-105.

S. Becker, K. Tabelow, H.U. Voss, A. Anwander, R.M. Heidemann and J. Polzehl, Position-orientation adaptive smoothing of diffusion weighted magnetic resonance data (POAS), Medical Image Analysis, 16 (2012), pp. 1142-1155.

J. Polzehl and K. Tabelow, Beyond the diffusion tensor model: The package dti, Journal of Statistical Software, 44 no. 12 (2011) pp. 1-26.

K. Tabelow, H.U. Voss and J. Polzehl, Modeling the orientation distribution function by mixtures of angular central Gaussian distributions, Journal of Neuroscience Methods, 203 (2012), pp. 200-211.

J. Polzehl and K. Tabelow, Structural adaptive smoothing in diffusion tensor imaging: The R package dti, Journal of Statistical Software, 31 (2009) pp. 1--24.

K. Tabelow, J. Polzehl, V. Spokoiny and H.U. Voss. Diffusion Tensor Imaging: Structural adaptive smoothing, NeuroImage 39(4), 1763-1773 (2008).

See Also

fmri aws oro.nifti

Examples

# NOT RUN {
  
# }
# NOT RUN {
demo(dti_art)
# }
# NOT RUN {
  
# }
# NOT RUN {
demo(mixtens_art)
# }