nilearn.image: Image Processing and Resampling Utilities

Mathematical operations working on Niimg-like objects like a (3+)D block of data, and an affine.

Functions:

binarize_img(img[, threshold, mask_img])	Binarize an image such that its values are either 0 or 1.
clean_img(imgs[, runs, detrend, ...])	Improve SNR on masked fMRI signals.
concat_imgs(niimgs[, dtype, ensure_ndim, ...])	Concatenate a list of 3D/4D niimgs of varying lengths.
coord_transform(x, y, z, affine)	Convert the x, y, z coordinates from one image space to another
copy_img(img)	Copy an image to a nibabel.Nifti1Image.
crop_img(img[, rtol, copy, pad, return_offset])	Crops an image as much as possible.
get_data(img)	Get the image data as a numpy.ndarray.
high_variance_confounds(imgs[, n_confounds, ...])	Return confounds signals extracted from input signals with highest variance.
index_img(imgs, index)	Indexes into a 4D Niimg-like object in the fourth dimension.
iter_img(imgs)	Iterates over a 4D Niimg-like object in the fourth dimension.
largest_connected_component_img(imgs)	Return the largest connected component of an image or list of images.
load_img(img[, wildcards, dtype])	Load a Niimg-like object from filenames or list of filenames.
math_img(formula, **imgs)	Interpret a numpy based string formula using niimg in named parameters.
mean_img(imgs[, target_affine, ...])	Compute the mean of the images over time or the 4th dimension.
new_img_like(ref_niimg, data[, affine, ...])	Create a new image of the same class as the reference image
resample_img(img[, target_affine, ...])	Resample a Niimg-like object
resample_to_img(source_img, target_img[, ...])	Resample a Niimg-like source image on a target Niimg-like image (no registration is performed: the image should already be aligned).
reorder_img(img[, resample])	Returns an image with the affine diagonal (by permuting axes).
smooth_img(imgs, fwhm)	Smooth images by applying a Gaussian filter.
swap_img_hemispheres(img)	Performs swapping of hemispheres in the indicated NIfTI image.
threshold_img(img, threshold[, ...])	Threshold the given input image, mostly statistical or atlas images.