Create a dataset from an fMRI timeseries image.
The timeseries image serves as the samples data, with each volume becoming a sample. All 3D volume samples are flattened into one-dimensional feature vectors, optionally being masked (i.e. subset of voxels corresponding to non-zero elements in a mask image).
In addition to (optional) samples attributes for targets and chunks the returned dataset contains a number of additional attributes:
Samples attributes (per each volume):
- volume index (time_indices)
- volume acquisition time (time_coord)
Feature attributes (per each voxel):
- voxel indices (voxel_indices), sometimes referred to as ijk
Dataset attributes:
- dump of the image (e.g. NIfTI) header data (imghdr)
- class of the image (e.g. Nifti1Image) (imgtype)
- volume extent (voxel_dim)
- voxel extent (voxel_eldim)
The default attribute name is listed in parenthesis, but may be altered by the corresponding prefix arguments. The validity of the attribute values relies on correct settings in the NIfTI image header.
Parameters : | samples : str or NiftiImage or list
targets : scalar or sequence
chunks : scalar or sequence
mask : str or NiftiImage
sprefix : str or None
tprefix : str or None
add_fa : dict or None
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Returns : | Dataset : |