code: def params_to_cti_params(result, min_diffusivity=0):
      # Extracting the diffusion tensor parameters from solution
      DT_elements = result[:6]
      evals, evecs = decompose_tensor(
          from_lower_triangular(DT_elements),
          min_diffusivity=min_diffusivity,
      )
      # Extracting kurtosis tensor parameters from solution
      MD_square = evals.mean(0) ** 2
      KT_elements = (
          result[6:21] / MD_square if MD_square else 0.0 * result[6:21]
      )
  
      # Extracting correlation tensor parameters from solution
      CT_elements = result[21:42]
  
      # Write output
      cti_params = np.concatenate(
          (
              evals,
              evecs[0],
              evecs[1],
              evecs[2],
              KT_elements,
              CT_elements,
          ),
          axis=0,
      )
  
      return cti_params
  
imports: import numpy
  from dipy.reconst.multi_voxel import multi_voxel_fit
  from dipy.reconst.base import ReconstModel
  from dipy.reconst.utils import cti_design_matrix
  from dipy.reconst.dki import DiffusionKurtosisFit
  from dipy.reconst.dti import decompose_tensor, from_lower_triangular, lower_triangular, MIN_POSITIVE_SIGNAL
  from dipy.core.onetime import auto_attr
label_desc: Use image node_id 5 for calling a global function with example usage: params_to_cti_params(result, min_diffusivity) and returns: cti_params