nilearn.regions: Operating on Regions

The nilearn.regions class module includes region extraction procedure on a 4D statistical/atlas maps and its function.

Functions:

connected_regions(maps_img[, ...])	Extraction of brain connected regions into separate regions.
connected_label_regions(labels_img[, ...])	Extract connected regions from a brain atlas image defined by labels (integers).
img_to_signals_labels(imgs, labels_img[, ...])	Extract region signals from image.
signals_to_img_labels(signals, labels_img[, ...])	Create image from region signals defined as labels.
img_to_signals_maps(imgs, maps_img[, mask_img])	Extract region signals from image.
signals_to_img_maps(region_signals, maps_img)	Create image from region signals defined as maps.

Classes:

RegionExtractor(maps_img[, mask_img, ...])	Class for brain region extraction.
Parcellations(method[, n_parcels, ...])	Learn parcellations on fMRI images.
ReNA(mask_img[, n_clusters, scaling, ...])	Recursive Neighbor Agglomeration (ReNA): Recursively merges the pair of clusters according to 1-nearest neighbors criterion.
HierarchicalKMeans(n_clusters[, init, ...])	Hierarchical KMeans: First clusterize the samples into big clusters.