code: def _applytfms(args):
      
      import nibabel as nb
      from nipype.utils.filemanip import fname_presuffix
      from niworkflows.interfaces.fixes import FixHeaderApplyTransforms as ApplyTransforms
  
      in_file, in_xform, ifargs, index, newpath = args
      out_file = fname_presuffix(in_file, suffix='_xform-%05d' % index,
                                 newpath=newpath, use_ext=True)
  
      copy_dtype = ifargs.pop('copy_dtype', False)
      xfm = ApplyTransforms(
          input_image=in_file, transforms=in_xform, output_image=out_file, **ifargs)
      xfm.terminal_output = 'allatonce'
      xfm.resource_monitor = False
      runtime = xfm.run().runtime
  
      if copy_dtype:
          nii = nb.load(out_file)
          in_dtype = nb.load(in_file).get_data_dtype()
  
          # Overwrite only iff dtypes don't match
          if in_dtype != nii.get_data_dtype():
              nii.set_data_dtype(in_dtype)
              nii.to_filename(out_file)
  
      return (out_file, runtime.cmdline)
docs: Applies ANTs' antsApplyTransforms to the input image.
      All inputs are zipped in one tuple to make it digestible by
      multiprocessing's map