dti-class                package:dti                R Documentation

_C_l_a_s_s "_d_t_i"

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

     The family of '"dti"' classes is used for Diffusion Weighted
     Imaging (DWI) data and, within the Diffusion Tensor Model (DTI),
     diffusion tenors and its indices.

_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:

     '"dti"' is only a superclass, no instances should be created.
     However, objects can be created by calls of the form 'new("dti",
     ...)'. '"dtiData"', '"dtiTensor"', and '"dtiIndices"' can be
     created from their correspondingly named functions and methods.

_S_l_o_t_s:


      '._D_a_t_a':  Object of class '"list"', usually empty. 

      '_b_t_b':  Object of class '"matrix"', matrix of dimension
          'c(6,ngrad)' obtained from gradient directions. 

      '_n_g_r_a_d':  Object of class '"integer"', number of gradients
          (including zero gradients). 

      '_s_0_i_n_d':  Object of class '"integer"', index of zero gradients
          within the sequence '1:ngrad'. 

      '_r_e_p_l_i_n_d':  Object of class '"integer"', index (identifier) of
          unique gradient directions. Used to characterize replications
          in the gradient design by identical indices. length is
          'ngrad'. 

      '_d_d_i_m':  Object of class '"integer"', dimension of subcube
          defined by 'xind', 'yind' and 'zind'. 

      '_d_d_i_m_0':  Object of class '"integer"', dimension of original
          image cubes. Vector of length 3. 

      '_x_i_n_d', '_y_i_n_d', '_z_i_n_d': Objects of class '"integer"', index for
          subcube definition in x-, y- and z-direction. 

      '_v_o_x_e_l_e_x_t':  Object of class '"numeric"', voxel extensions in x-,
          y- and z-direction. Vector of length 3. 

      '_o_r_i_e_n_t_a_t_i_o_n':  Object of class '"integer"', orientation of data
          according to AFNI convention. Vector of length 3. 

      '_l_e_v_e_l':  Object of class '"numeric"', minimal valid S0-level. No
          evaluation will be performed for voxels with S0-values less
          than 'level'.  

      '_s_o_u_r_c_e':  Object of class '"character"', name of the source
          imgage file or source directory. 

      '_c_a_l_l':  Object of class '"call"', call that created the object. 

     For class '"dtiData"':


      '_s_i':  Object of class '"array"', Diffusion Weighted Data. 

      '_s_d_c_o_e_f':  Object of class '"numeric"', Parameters of the model
          for error  standard deviation as a function of the mean.
          First two entries refer to intercept and slope of a linear
          function, third and fourth value are the endpoints of the
          interval of linearity. Contains 'rep(0,4)' if not set. If the
          function 

     For class '"dtiTensor"':


      '_D':  Object of class '"array"', estimated tensors, dimension
          'c(6,ddim)'. Tensors are stored as upper diagonal matrices. 

      '_t_h_0':  Object of class '"array"', estimated intensities in S0
          images, dimension 'ddim' 

      '_s_i_g_m_a':  Object of class '"array"', estimated error variances if
          'method=="linear"', zero otherwise. 

      '_s_c_o_r_r':  Object of class '"numeric"', estimated spatial
          correlations in coordinate directions 

      '_b_w':  Object of class '"numeric"', bandwidth for a Gaussian
          kernel that approximately creates the estimated spatial
          correlations. Needed for adjustments of critical values in
          the adaptive smoothing algorithm used in function
          'dti.smooth' 

      '_m_a_s_k':  Object of class '"array"', logical indicating the voxel
          where the tensor was estimated. 

      '_h_m_a_x':  Object of class '"numeric"', maximal bandwidth in case
          of adaptive smoothing, 1 otherwise. 

      '_o_u_t_l_i_e_r':  Object of class '"numeric"', index of voxel where
          physical constraints are not met, i.e. where the observed
          values in gradient images Si were larger than the
          corresponding S0 values. These are probably motion effects or
          registration errors. Values are replaced by the corresponding
          (mean) S0 values.

     '_s_c_a_l_e': Numerical value corresponding to the 95% quantile of the
          maximal eigenvalues of estimated tensors within the mask.
          Used for scaling in function 'show3d.dtiTensor'

      '_m_e_t_h_o_d':  Object of class '"character"', either '"linear"' or
          '"nonlinear"' or '"unknown"'. Indicates the regression model
          used for estimating the tensors.

     For class '"dtiIndices"':


      '_f_a':  Object of class '"array"', Fractional anisotropy values
          (FA)

      '_g_a':  Object of class '"array"', Geodetic anisotropy values (GA)

      '_m_d':  Object of class '"array"', Mean diffusivity values (MD) 

      '_a_n_d_i_r':  Object of class '"array"', Main directions of
          anisotropy 

      '_b_a_r_y':  Object of class '"array"', Shape parameters 

      '_m_e_t_h_o_d':  Object of class '"character"' either '"linear"' or
          '"nonlinear"' or '"unknown"'. Indicates the regression model
          used for estimating the tensors.

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

     Methods only operate on subclasses '"dtiData"', '"dtiTensor"', and
     '"dtiIndices"'.

     _d_t_i._s_m_o_o_t_h Create estimates of diffusion tensors in each voxel
          using structural adaptive spatial smoothing. 

     _d_t_i_T_e_n_s_o_r 'signature(object = "dtiData")': Create estimates of
          diffusion tensors in each voxel. 

     _d_t_i_I_n_d_i_c_e_s 'signature(object = "dtiTensor")': Create estimates of
          diffusion tensors indices in each voxel. 

     _p_l_o_t Method for Function `plot' in Package `dti'. 

     _p_r_i_n_t Method for Function `print' in Package `dti'. 

     _s_u_m_m_a_r_y Method for Function `summary' in Package `dti'. 

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

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

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

     'dtiData', 'readDWIdata', 'sdpar-methods', 'dtiTensor-methods', 
     'dti.smooth-methods', 'dtiIndices-methods', 'plot-methods',
     'print-methods', 'summary-methods', 'extract-methods'

