dtiTensor-methods            package:dti            R Documentation

_M_e_t_h_o_d_s _f_o_r _F_u_n_c_t_i_o_n _d_t_i_T_e_n_s_o_r _i_n _P_a_c_k_a_g_e _d_t_i

_D_e_s_c_r_i_p_t_i_o_n:

     The method estimates, in each voxel, the diffusion tensor from the
     DWI data contained in an object of class '"dtiData"'.

_U_s_a_g_e:

       ## S4 method for signature 'dtiData':
       dtiTensor(object, method="nonlinear", varmethod="replicates", varmodel="local")

_A_r_g_u_m_e_n_t_s:

  object: Object of class '"dtiData"'

  method: Method for tensor estimation. May be '"linear"', or
          '"nonlinear"'. 

varmethod: Specifies the method for estimating the error variance. May
          be '"replicates"'. 

varmodel: Specifies the model for the variance. May be '"global"', or
          '"local"'. 

_V_a_l_u_e:

     An object of class '"dtiTensor"'.

_M_e_t_h_o_d_s:



     _o_b_j = "_A_N_Y" Returns a warning. 

     _o_b_j = "_d_t_i_D_a_t_a" Estimate diffusion tensor from data in each voxel
          with the different options for the regression type and model
          for variance estimation.  If 'method=="linear"' estimates are
          obtained using a linearization of the tensor model. This was
          the estimate used in Tabelow et.al. (2008). 
          'method=="nonlinear"' uses a nonlinear regression model with
          reparametrization that ensures the tensor to be  positive
          semidefinite, see  Koay et.al. (2006).  If
          'varmethod=="replicates"' the error variance is estimated
          from replicated gradient directions if possible, otherwise an
          estimate is obtained from the residual sum of squares.  If
          'varmodel=="global"' a homogeneous variance is assumed and
          estimated as the median of the local variance estimates. 


_A_u_t_h_o_r(_s):

     Karsten Tabelow tabelow@wias-berlin.de
       J\"org Polzehl polzehl@wias-berlin.de

_R_e_f_e_r_e_n_c_e_s:

     K. Tabelow, J. Polzehl, H.U. Voss, and V. Spokoiny.  _Diffusion
     Tensor Imaging: Structural adaptive smoothing_,  NeuroImage 39(4),
     1763-1773 (2008).

     C.G. Koay, J.D. Carew, A.L. Alexander, P.J. Basser and M.E.
     Meyerand. _ Investigation of Anomalous Estimates of Tensor-Derived
     Quantities in Diffusion Tensor Imaging_,  Magnetic Resonance in
     medicine, 2006, 55, 930-936.

     <URL:  http://www.wias-berlin.de/projects/matheon_a3/>

_S_e_e _A_l_s_o:

     'dtiData',  'readDWIdata',  'dtiIndices-methods',   'medinria', 
     'dtiData',  'dtiTensor'

_E_x_a_m_p_l_e_s:

       ## Not run: demo(dti_art)

