docstr: Random crop with different methods:
docstr_tok: ["Random","crop","with","different","methods",":"]
code: def __crop_data__(self, data, label):
      """
      Random crop with different methods:
      """
      # random center crop
      data, label = self.__random_center_crop__(data, label)
  
      return data, label
  
file_path: MedicalNet/datasets/brains18.py
imports: import math
  import os
  import random
  import numpy
  from torch.utils.data import Dataset
  import nibabel
  from scipy import ndimage
label_desc: Use image node_id 9 for calling the BrainS18Dataset obj's underlying member method code with example usage: obj.__crop_data__(data, label) and returns: data,  label