Note
This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.
nilearn.regions.img_to_signals_labels#
- nilearn.regions.img_to_signals_labels(imgs, labels_img, mask_img=None, background_label=0, order='F', strategy='mean', keep_masked_labels=True, return_masked_atlas=False)[source]#
Extract region signals from image.
This function is applicable to regions defined by labels.
labels, imgs and mask shapes and affines must fit. This function performs no resampling.
- Parameters:
- imgs
list
of Niimg-like objects See Input and output: neuroimaging data representation. Input images.
- labels_imgNiimg-like object
See Input and output: neuroimaging data representation. Regions definition as labels. By default, the label zero is used to denote an absence of region. Use background_label to change it.
- mask_imgNiimg-like object, optional
See Input and output: neuroimaging data representation. Mask to apply to labels before extracting signals. Every point outside the mask is considered as background (i.e. no region).
- background_labelnumber, default=0
Number representing background in labels_img.
- order
str
, default=”F” Ordering of output array (“C” or “F”).
- strategy
str
, default=”mean” The name of a valid function to reduce the region with. Must be one of: sum, mean, median, minimum, maximum, variance, standard_deviation.
- keep_masked_labels
bool
, default=True When a mask is supplied through the “mask_img” parameter, some atlas regions may lie entirely outside of the brain mask, resulting in empty time series for those regions. If True, the masked atlas with these empty labels will be retained in the output, resulting in corresponding time series containing zeros only. If False, the empty labels will be removed from the output, ensuring no empty time series are present.
Deprecated since version 0.10.2: The ‘True’ option for
keep_masked_labels
is deprecated. The default value will change to ‘False’ in 0.13, and thekeep_masked_labels
parameter will be removed in 0.15.- return_masked_atlas
bool
, default=False If True, the masked atlas is returned. deprecated in version 0.13, to be removed in 0.15. after 0.13, the masked atlas will always be returned.
- imgs
- Returns:
- signals
numpy.ndarray
Signals extracted from each region. One output signal is the mean of all input signals in a given region. If some regions are entirely outside the mask, the corresponding signal is zero. Shape is: (scan number, number of regions)
- labels
list
ortuple
Corresponding labels for each signal. signal[:, n] was extracted from the region with label labels[n].
- masked_atlasNiimg-like object
Regions definition as labels after applying the mask. returned if return_masked_atlas is True.
- signals
See also
nilearn.regions.signals_to_img_labels
nilearn.regions.img_to_signals_maps
nilearn.maskers.NiftiLabelsMasker
Signal extraction on labels images e.g. clusters