code: def __init__(
      self,
      model_dir,
      network,
      roi_size=(96, 96, 96),
      target_spacing=(1.0, 1.0, 1.0),
      description="Train Segmentation model for spleen",
      **kwargs,
  ):
      self._network = network
      self.roi_size = roi_size
      self.target_spacing = target_spacing
      super().__init__(model_dir, description, **kwargs)
  
file_path: MONAILabel/sample-apps/radiology/lib/trainers/segmentation_spleen.py
imports: import logging
  import torch
  from monai.apps.deepedit.transforms import NormalizeLabelsInDatasetd
  from monai.inferers import SlidingWindowInferer
  from monai.losses import DiceCELoss
  from monai.transforms import Activationsd, AsDiscreted, EnsureChannelFirstd, EnsureTyped, LoadImaged, Orientationd, RandSpatialCropd, ScaleIntensityd, ScaleIntensityRanged, SelectItemsd, Spacingd, ToTensord
  from monailabel.tasks.train.basic_train import BasicTrainTask, Context
label_desc: Use image node_id 1 to create a new SegmentationSpleen object from inherited base classes: BasicTrainTask with example: obj = SegmentationSpleen(model_dir, network, roi_size, target_spacing, description)