# nilearn.image: Image Processing and Resampling Utilities#

Mathematical operations working on Niimg-like objects.

Like, for example, 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 space. 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 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) Iterate over a 4D Niimg-like object in the fourth dimension. 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[, copy_header_from]) 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. reorder_img(img[, resample]) Return an image with the affine diagonal (by permuting axes). smooth_img(imgs, fwhm) Smooth images by applying a Gaussian filter. swap_img_hemispheres(img) Perform swapping of hemispheres in the indicated NIfTI image. threshold_img(img, threshold[, ...]) Threshold the given input image, mostly statistical or atlas images.