# Data details¶

The challenge this year focuses on the effect of the local reconstruction
accuracy on the quality of connectivity reconstruction. The phantom consists in
**a set of fiber bundles**, that connect one area of the “cortex” to another. There
is a wide range of configurations (branching, crossing, kissing), fiber bundles
radii, and fiber geometry.

## Signal simulation¶

Given the fiber configurations, the diffusion MR signal is simulated in each
voxel. To account for the **partial volume effect** (multiple fiber compartments
within the same imaging voxel), we use an approach similar to the Numerical
Fiber Generator [Close2009].

As for the local model of diffusion, the signal is simulated considering
hindered and restricted diffusion, to account for **extra-axonal and intra-axonal
diffusion**. Finally, depending on the position in space, there is also an
isotropic compartment, to account for the **CSF contamination** close to the
ventricles in brain imaging.

## Noise simulation¶

The magnitude MR signal is corrupted by **Rician noise**. If is
the noise-free diffusion weighted signal, then the signal is simulated as

where and , are independent, zero-mean Gaussian distributed with the same covariance .

## Data format¶

The simulated signal for a given SNR and a given acquisition scheme is provided
as a **4D Nifti image**.

References

[Close2009] | Thomas G. Close et al., A software tool to generate simulated white matter structures for the assessment of fibre-tracking algorithms, NeuroImage (2009). |