code: def get_2d_slice(image, view: int, is_label):
      """If image is 3d, get the central slice. If is already 2d, return as-is.
      If image is label, set 0 to np.nan.
      """
      if image.ndim == 2:
          out = image
      else:
          shape = image.shape
          slices = [slice(0, s) for s in shape]
          _slice = shape[view] // 2
          slices[view] = slice(_slice, _slice + 1)
          out = np.squeeze(image[tuple(slices)], view)
      if is_label:
          out[out == 0] = np.nan
      return out
  
imports: from __future__ import annotations
  import os
  import pathlib
  import tempfile
  import textwrap
  from copy import deepcopy
  from glob import glob
  from typing import TYPE_CHECKING
  import numpy
  import torch
  from monai.apps import download_and_extract
  from monai.transforms import Affine, Affined, AsDiscrete, Compose, EnsureChannelFirstd, Flip, Flipd, LoadImaged, MapTransform, Orientation, Orientationd, Rand3DElastic, Rand3DElasticd, RandFlip, RandFlipd, Randomizable, RandRotate, RandRotated, RandZoom, RandZoomd, Rotate, Rotate90, Rotate90d, Rotated, ScaleIntensity, ScaleIntensityd, SpatialPadd, Zoom, Zoomd
  from monai.transforms.croppad.array import BorderPad, CenterScaleCrop, CenterSpatialCrop, CropForeground, DivisiblePad, RandCropByLabelClasses, RandCropByPosNegLabel, RandScaleCrop, RandSpatialCrop, RandSpatialCropSamples, RandWeightedCrop, ResizeWithPadOrCrop, SpatialCrop, SpatialPad
  from monai.transforms.croppad.dictionary import BorderPadd, CenterScaleCropd, CenterSpatialCropd, CropForegroundd, DivisiblePadd, RandCropByLabelClassesd, RandCropByPosNegLabeld, RandScaleCropd, RandSpatialCropd, RandSpatialCropSamplesd, RandWeightedCropd, ResizeWithPadOrCropd, SpatialCropd
  from monai.transforms.intensity.array import AdjustContrast, ForegroundMask, GaussianSharpen, GaussianSmooth, GibbsNoise, HistogramNormalize, KSpaceSpikeNoise, MaskIntensity, MedianSmooth, NormalizeIntensity, RandAdjustContrast, RandBiasField, RandCoarseDropout, RandCoarseShuffle, RandGaussianNoise, RandGaussianSharpen, RandGaussianSmooth, RandGibbsNoise, RandHistogramShift, RandKSpaceSpikeNoise, RandRicianNoise, RandScaleIntensity, RandShiftIntensity, RandStdShiftIntensity, SavitzkyGolaySmooth, ScaleIntensityRange, ScaleIntensityRangePercentiles, ShiftIntensity, StdShiftIntensity, ThresholdIntensity
  from monai.transforms.intensity.dictionary import AdjustContrastd, ForegroundMaskd, GaussianSharpend, GaussianSmoothd, GibbsNoised, HistogramNormalized, KSpaceSpikeNoised, MaskIntensityd, MedianSmoothD, NormalizeIntensityd, RandAdjustContrastd, RandBiasFieldd, RandCoarseDropoutd, RandCoarseShuffled, RandGaussianNoised, RandGaussianSharpend, RandGaussianSmoothd, RandGibbsNoised, RandHistogramShiftd, RandKSpaceSpikeNoised, RandRicianNoised, RandScaleIntensityd, RandShiftIntensityd, RandStdShiftIntensityd, SavitzkyGolaySmoothd, ScaleIntensityRanged, ScaleIntensityRangePercentilesd, ShiftIntensityd, StdShiftIntensityd, ThresholdIntensityd
  from monai.transforms.post.array import KeepLargestConnectedComponent, LabelFilter, LabelToContour, RemoveSmallObjects
  from monai.transforms.post.dictionary import AsDiscreted, KeepLargestConnectedComponentd, LabelFilterd, LabelToContourd, RemoveSmallObjectsd
  from monai.transforms.smooth_field.array import RandSmoothDeform, RandSmoothFieldAdjustContrast, RandSmoothFieldAdjustIntensity
  from monai.transforms.smooth_field.dictionary import RandSmoothDeformd, RandSmoothFieldAdjustContrastd, RandSmoothFieldAdjustIntensityd
  from monai.transforms.spatial.array import GridDistortion, Rand2DElastic, RandAffine, RandAxisFlip, RandGridDistortion, RandRotate90, Resize, Spacing
  from monai.transforms.spatial.dictionary import GridDistortiond, Rand2DElasticd, RandAffined, RandAxisFlipd, RandGridDistortiond, RandRotate90d, Resized, Spacingd
  from monai.utils.enums import CommonKeys
  from monai.utils.misc import MONAIEnvVars
  from monai.utils.module import optional_import
label_desc: Use image node_id 4 for calling a global function with example usage: get_2d_slice(image, view, is_label) and returns: out