# `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. 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. Performs swapping of hemispheres in the indicated NIfTI image. `threshold_img`(img, threshold[, ...]) Threshold the given input image, mostly statistical or atlas images.