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.

8.8.5. nilearn.regions.img_to_signals_maps

nilearn.regions.img_to_signals_maps(imgs, maps_img, mask_img=None)

Extract region signals from image.

This function is applicable to regions defined by maps.

Parameters:

imgs: Niimg-like object

See http://nilearn.github.io/manipulating_images/input_output.html Input images.

maps_img: Niimg-like object

See http://nilearn.github.io/manipulating_images/input_output.html regions definition as maps (array of weights). shape: imgs.shape + (region number, )

mask_img: Niimg-like object

See http://nilearn.github.io/manipulating_images/input_output.html mask to apply to regions before extracting signals. Every point outside the mask is considered as background (i.e. outside of any region).

order: str

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

Returns:

region_signals: numpy.ndarray

Signals extracted from each region. Shape is: (scans number, number of regions intersecting mask)

labels: list

maps_img[…, labels[n]] is the region that has been used to extract signal region_signals[:, n].

See also

nilearn.regions.img_to_signals_labels, nilearn.regions.signals_to_img_maps

nilearn.input_data.NiftiMapsMasker

Signal extraction on probabilistic maps e.g. ICA