class_docstr: This class is intended for the Synb0 model.
  The model is the deep learning part of the Synb0-Disco
  pipeline, thus stand-alone usage is not
  recommended.
docstr: The model was pre-trained for usage on pre-processed images
  following the synb0-disco pipeline.
  One can load their own weights using load_model_weights.
  
  This model is designed to take as input
  a b0 image and a T1 weighted image.
  
  It was designed to predict a b-inf image.
  
  Parameters
  ----------
  verbose : bool (optional)
      Whether to show information about the processing.
      Default: False
  
  References
  ----------
  ..  [1] Schilling, K. G., Blaber, J., Huo, Y., Newton, A.,
      Hansen, C., Nath, V., ... & Landman, B. A. (2019).
      Synthesized b0 for diffusion distortion correction (Synb0-DisCo).
      Magnetic resonance imaging, 64, 62-70.
  ..  [2] Schilling, K. G., Blaber, J., Hansen, C., Cai, L.,
      Rogers, B., Anderson, A. W., ... & Landman, B. A. (2020).
      Distortion correction of diffusion weighted MRI without reverse
      phase-encoding scans or field-maps.
      PloS one, 15(7), e0236418.
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code: def __init__(self, verbose=False):
      r"""
      The model was pre-trained for usage on pre-processed images
      following the synb0-disco pipeline.
      One can load their own weights using load_model_weights.
  
      This model is designed to take as input
      a b0 image and a T1 weighted image.
  
      It was designed to predict a b-inf image.
  
      Parameters
      ----------
      verbose : bool (optional)
          Whether to show information about the processing.
          Default: False
  
      References
      ----------
      ..  [1] Schilling, K. G., Blaber, J., Huo, Y., Newton, A.,
          Hansen, C., Nath, V., ... & Landman, B. A. (2019).
          Synthesized b0 for diffusion distortion correction (Synb0-DisCo).
          Magnetic resonance imaging, 64, 62-70.
      ..  [2] Schilling, K. G., Blaber, J., Hansen, C., Cai, L.,
          Rogers, B., Anderson, A. W., ... & Landman, B. A. (2020).
          Distortion correction of diffusion weighted MRI without reverse
          phase-encoding scans or field-maps.
          PloS one, 15(7), e0236418.
      """
  
      if not have_tf:
          raise tf()
      if not have_tfa:
          raise tfa()
  
      log_level = "INFO" if verbose else "CRITICAL"
      set_logger_level(log_level, logger)
  
      # Synb0 network load
  
      self.model = UNet3D(input_shape=(80, 80, 96, 2))
  
imports: import logging
  import numpy
  from dipy.data import get_fnames
  from dipy.testing.decorators import doctest_skip_parser
  from dipy.utils.optpkg import optional_package
  from dipy.nn.utils import normalize, unnormalize, set_logger_level
label_desc: Use image node_id 1 to create a new Synb0 object  with example: obj = Synb0(verbose)