code: def from_qte_to_cti(C):
      """
      Rescales the qte C elements to the C elements used in CTI.
  
      Parameters
      ----------
      C: array(..., 21)
          Twenty-one elements of the covariance tensor in voigt notation plus
          some extra scaling factors.
  
      Returns
      -------
      ccti: array(..., 21)
          Covariance Tensor Elements with no hidden factors.
      """
      const = np.sqrt(2)
      ccti = np.zeros((21, 1))
      ccti[0] = C[0]
      ccti[1] = C[1]
      ccti[2] = C[2]
      ccti[3] = C[3] / const
      ccti[4] = C[4] / const
      ccti[5] = C[5] / const
      ccti[6] = C[6] / 2
      ccti[7] = C[7] / 2
      ccti[8] = C[8] / 2
      ccti[9] = C[9] / 2
      ccti[10] = C[10] / 2
      ccti[11] = C[11] / 2
      ccti[12] = C[12] / 2
      ccti[13] = C[13] / 2
      ccti[14] = C[14] / 2
      ccti[15] = C[15] / 2
      ccti[16] = C[16] / 2
      ccti[17] = C[17] / 2
      ccti[18] = C[18] / (2 * const)
      ccti[19] = C[19] / (2 * const)
      ccti[20] = C[20] / (2 * const)
      return ccti
  
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 1 for calling a global function with example usage: from_qte_to_cti(C) and returns: ccti