The data set consists of six transformed diffusion weighted images (DWI) showing a representative axial slice of the human brain. The stored values can directly be passed to estimate the diffusion tensor elements (regression coefficients) using a transform of the applied gradients as regressors.

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The first two dimensions provide the transformed signal intensities of
one brain slice sized 90 *x* 75 voxels. The third
dimension encodes for the direction of the six applied diffusion
weighting gradients.

The present DTI data set was acquired at 1.5 T (Signa Echospeed; GE
Medical Systems) using a spin-echo echo-planar sequence with TR/TE =
4200ms/120ms and diffusion gradients in a six noncollinear directions
with a b-value of 880 s/mm*^2*. One axial
slice was selected from a volume of six DWI (b = 880
s/mm*^*2) and one reference image (b = 0
s/mm*^*2). In-plane resolution amounts to
1.875 *x* 1.875 mm*^*2.

The transformation of the raw signal intensities,

*y = - 1/b
log(S_i/S_0)*

is derived from the Stejskal-Tanner equation and is proposed by Papadakis et al.

Diffusion Tensor Imaging was performed at the Max-Planck-Institute of Psychiatry, Munich, Germany.

Basser P. J. and Jones D. K. (2002) Diffusion-tensor MRI: Theory,
experimental design and data analysis – a technical review. *NMR
in Biomedicine* **15**, 456-467.

Mori S. and Barker P. B. (1999) Diffusion magnetic resonance imaging:
Its principle and applications. *The Anatomical Record*
**257**, 102-109.

Papadakis N. G., Xing D., Huang C. L.-H., Hall L. and Carpenter T. A. (1999). A comparative study of acquisition schemes for diffusion tensor imaging using MRI. Journal of Magnetic Resonance 137, 67-82.

Stejskal E. O. and Tanner J. E. (1965) Spin diffusion measurements:
Spin echoes in the presence of time-dependent field
gradient. *The Journal of Chemical Physics* **42**, 288-292.

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