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.

8.8.4. nilearn.regions.signals_to_img_labels

nilearn.regions.signals_to_img_labels(signals, labels_img, mask_img=None, background_label=0, order='F')

Create image from region signals defined as labels.

The same region signal is used for each voxel of the corresponding 3D volume.

labels_img, mask_img must have the same shapes and affines.

Parameters:

signals: numpy.ndarray

2D array with shape: (scan number, number of regions in labels_img)

labels_img: Niimg-like object

See http://nilearn.github.io/manipulating_images/input_output.html Region definitions using labels.

mask_img: Niimg-like object, optional

Boolean array giving voxels to process. integer arrays also accepted, In this array, zero means False, non-zero means True.

background_label: number

label to use for “no region”.

order: str

ordering of output array (“C” or “F”). Defaults to “F”.

Returns:

img: nibabel.Nifti1Image

Reconstructed image. dtype is that of “signals”, affine and shape are those of labels_img.

See also

nilearn.regions.img_to_signals_labels, nilearn.regions.signals_to_img_maps

nilearn.input_data.NiftiLabelsMasker

Signal extraction on labels images e.g. clusters