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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def smooth_image(image, sigma, sigma_in_physical_coordinates=True, FWHM=False, max_kernel_width=32):
 """ Smooth an image ANTsR function: `smoothImage` Arguments --------- image Image to smooth sigma Smoothing factor. Can be scalar, in which case the same sigma is applied to each dimension, or a vector of length dim(inimage) to specify a unique smoothness for each dimension. sigma_in_physical_coordinates : boolean If true, the smoothing factor is in millimeters; if false, it is in pixels. FWHM : boolean If true, sigma is interpreted as the full-width-half-max (FWHM) of the filter, not the sigma of a Gaussian kernel. max_kernel_width : scalar Maximum kernel width Returns ------- ANTsImage Example ------- """

    if image.components == 1:
        return _smooth_image_helper(image, sigma, sigma_in_physical_coordinates, FWHM, max_kernel_width)
    else:
        imagelist = utils.split_channels(image)
        newimages = []
        for image in imagelist:
            newimage = _smooth_image_helper(image, sigma, sigma_in_physical_coordinates, FWHM, max_kernel_width)
            newimages.append(newimage)
        return utils.merge_channels(newimages)