gdimap (version 0.1-9)

gqi.odfpeaks: Main Fibre Orientation Determination via Peak Detection with GQI Reconstruction

Description

Generalized q-Sampling Imaging (GQI) is used for orientation distribution function (ODF) reconstruction. For identifying voxel fibre directions, the local maxima of the reconstructed ODF are identified, where this function surpasses a certain threshold.

Usage

gqi.odfpeaks(gdi="gqi", fbase=NULL, rg=NULL, swap=FALSE, lambda=NULL,
 depth=3, btoption=2, threshold=0.4, showglyph=FALSE, bview="coronal",
 savedir=tempdir(), aniso=NULL)

Arguments

gdi

method of ODF reconstruction to use c("gqi", "gqi2") (default: "gqi").

fbase

Directory where the required input data files are located.

rg

range of slices to process; default option rg=NULL processes all slices.

swap

toggle radiological/neurological orientation (default: FALSE).

lambda

diffusion sampling length in gdi="gqi" and gdi="gqi2". By default the following default values are used when lambda=NULL is specified: 1.24 in "gqi", 3 in "gqi2".

depth

sampling density on the hemisphere used in simulation (default N=321; depth=3).

btoption

b-table selection between btable.txt (btoption=1), and 3D-DSI grid b-table supplied with the diffusion data set (default btoption=2).

threshold

thresholding generalized fractional anisotropy (GFA) value at each voxel (default: 0.4).

showglyph

logical variable controlling visualization of voxel glyphs (default: FALSE).

bview

MRI slice view selection in {axial, coronal, sagittal} (default: "coronal").

savedir

directory for saving/loading processed results (default: tempdir().

aniso

anisotropic parameter in the range "[0,1)" or NULL to use in ODF pos-processing default: NULL.

Value

• gqi.odfpeaks outputs two data files in NIfTI format named data_V1_gqi.nii.gz and data_gfa_gqi.nii.gz. The first main fibre directions per voxel are contained in data_V1_gqi.nii.gz. The file data_gfa_gqi.nii.gz contains the GFA values per voxel.

concept

• Diffusion Magnetic Resonance
• GQI Reconstruction
• Orientation Distribution Function
• RGB maps

Details

GQI specifies an operational sampling scheme in q-space from which the ODF can be estimated. The most commonly used approach for identifying fibre directions is to extract the local maxima of the reconstructed ODF, where this function surpasses a certain threshold. The application of the approach is based on the assumption that the principal directions extracted from the ODF can be interpreted as principal directions of the underlying fibre architecture. Thresholding avoids selecting smaller ODF peaks that may appear due to noise. Local maxima of the reconstructed ODF are located simply by selecting a large number of sampled points on the sphere and searching within a fixed radius neighbourhood. GQI (Yeh et.al. 2010) or GQI2 (Garyfallidis 2012) may be used for ODF reconstruction.

Starting with the raw high angular resolution diffusion signal acquired on a grid of q-space, the ODF profile is reconstructed at each voxel, considering a sampling density of unit vectors on a unit S2 grid. Generalized q-Sampling Imaging (GQI) is used for orientation distribution function (ODF) reconstruction. Two b-tables defining the acquisition setup are specified. One is a b-table for a S2-like grid denoted by btable.txt. The other is the b-table for the 3D-DSI sampling scheme used in the DICOM data acquisition. This b-table has 203 points uniformly distributed on a 3D grid limited to the volume of the unit sphere. In both tables, the b-values range from 0 to 4000.

The output files data_V1_gqi.nii.gz and data_gfa_gqi.nii.gz are used to visualize RGB maps through rgbvolmap() or via the "FSL/fslview" tool. These files may also be used to perform white matter fibre tractography.

References

Ferreira da Silva, A. R. Computational Representation of White Matter Fiber Orientations, International Journal of Biomedical Imaging, Vol. 2013, Article ID 232143, Hindawi Publishing Corporation http://dx.doi.org/10.1155/2013/232143.

Ferreira da Silva, A. R. Facing the Challenge of Estimating Human Brain White Matter Pathways. In Proc. of the 4th International Joint Conference on Computational Intelligence (Oct. 2012), K. Madani, J. Kacprzyk, and J. Filipe, Eds., SciTePress, pp. 709-714.

Jenkinson, M., Beckmann, C. F., Behrens, T. E., Woolrich, M. W., and Smith, S. M. FSL. NeuroImage 62, 2 (2012), 782-790.

See Also

gqi.odfpeaklines, plotglyph, gqi.odfvmf, gqi.odfvmflines, gqi.odfvxgrid, s2tessel.zorder, rgbvolmap, simulglyph.vmf, simul.fandtasia, simul.simplefield, data, data.bval, data.bvec, btable

Examples

##-------------
    ## Generate ODF volumes (GQI volume processing) for
    ## range of slices using deterministic find peaks algorithm
    gqi.odfpeaks(rg=c(1,1), bview="coronal", showglyph=FALSE)
    ## Show RGB maps for range of slices processed by gqi.odfpeaks()
    rgbvolmap(fbase=tempdir())
    ##-------------
    ## Process whole volume: generate NIfTI files
    ##   data_gfa_gqi.nii.gz and data_V1_gqi.nii.gz
    gqi.odfpeaks(rg=NULL)
    rgbvolmap(fbase=tempdir(), rg=NULL, bview="coronal")
    ##-------------
    ## Visualization of RBG maps based on processed volumes
    ## "data_gfa_gqi.nii.gz and "data_V1_gqi.nii.gz"
    ## (visualization compatible with the FSL/fslview tool) 
    rgbvolmap(rg=NULL, bview="coronal")
    ##-------------
    ## Show reconstructed glyphs in ODF processing 
    ## for principal direction determination
    gqi.odfpeaks(rg=c(1,1), bview="coronal", showglyph=TRUE, depth=3)