R: Methods for Function 'tracking' in Package 'dti'

tracking-methods {dti}

R Documentation

Methods for Function ‘tracking’ in Package ‘dti’

Description

The function provides fiber tracking of "dtiTensor", "dtiIndices", and "dwiMixtensor" objects and methods for fiber manipulations.

Usage

## S4 method for signature 'dtiTensor'
tracking(obj, roix=NULL, roiy=NULL, roiz=NULL, mask=NULL,
                    method="LINEPROP", minfa=0.3, maxangle=30, subsample = 1)
## S4 method for signature 'dtiIndices'
tracking(obj, roix=NULL, roiy=NULL, roiz=NULL, mask=NULL,
                    method="LINEPROP", minfa=0.3, maxangle=30, subsample = 1)
## S4 method for signature 'dwiMixtensor'
tracking(obj, roix=NULL, roiy=NULL, roiz=NULL, mask=NULL,
                    method="LINEPROP", minfa=0.3, maxangle=30, subsample = 1,
                    mincompartsize = 0)
## S4 method for signature 'dwiFiber'
selectFibers(obj, roix=NULL, roiy=NULL, roiz=NULL, mask=NULL,
                    minlength=1)
## S4 method for signature 'dwiFiber'
reduceFibers(obj, maxdist=1, ends=TRUE)

## S4 method for signature 'dwiFiber,dwiFiber'
combineFibers(obj, obj2)

## S4 method for signature 'dwiFiber,dwiFiber'
touchingFibers(obj, obj2, maxdist=1, combine=FALSE)

Arguments

`obj`	An object of class `"dtiTensor"`, `"dtiIndices"`, or `"dwiMixtensor"` for tracking() and `"dwiFiber"` for selectFiber(), conbineFibers().
`obj2`	An object of class `"dwiFiber"` for combineFibers().
`roix`	Indices defining the ROI in x direction. Currently min/max is used to define ROIx
`roiy`	Indices defining the ROI in y direction. Currently min/max is used to define ROIy
`roiz`	Indices defining the ROI in z direction. Currently min/max is used to define ROIz
`mask`	Mask defining seed points for tracking
`method`	Method for fibre tracking. "LINEPROP" is simple line propagation algorithm which is the default.
`minfa`	Minimal FA to follow the tracks. default 0.3
`maxangle`	Maximal angle between fiber in adjacent voxels. default 30 degree.
`subsample`	Subsampling order of the data to get more dense fibre tracks. Note, that objects become very(!) large.
`minlength`	Minimal length of fibers to be selected.
`maxdist`	Maximal supremum distance between fibers in mm
`ends`	Logical: Use only endpoints of shorter fibers for distance (TRUE) or compute distances using full fiber-length (FALSE). Default (TRUE) removes more fibers and is significantly faster.
`mincompartsize`	Minimal size of a compartment in dwiMixtensor that will be used in fiber tracking.
`combine`	If `combine=TRUE` fibers selected from `obj` are combined with the fibers from `obj2`.

Value

The function returns an object of class dwiFiber.

Methods

obj = "dtiTensor": Fiber tracking is performed on the estimated vector field of principal diffusion direction using the method method. Currently only line propagation is implemented. The resulting tracks can be visualized using function show3d

obj = "dtiIndices": Fiber tracking is performed on the estimated vector field of principal diffusion direction using the method method. Currently only line propagation is implemented. The resulting tracks can be visualized using function show3d

obj = "dwiMixtensor": Fiber tracking is performed on the estimated vector fields of diffusion direction in the mixed tensor model using the method method. Currently only line propagation is implemented. The resulting tracks can be visualized using function show3d

obj = "dwiFiber": selectFibers produces a dwiFiber-object containing all fibers that cross the region of interest and exceed a minimum length. reduceFibers eliminates all fibers that are within a maximum supremum distance of maxdist mm of a longer fiber. reduceFibers allows to reduce the size of a dwiFiber-object considerably but is slow !
signature(obj1 = "dwiFiber", obj2 = "dwiFiber"): combineFibers produces a dwiFiber-object containing all fibers that are in one of the supplied objects. touchingFibers takes all fibers from obj that have a minimum distance to a fiber in obj2 of less than maxdist. If combine=TRUE these fibers are combined with the fibers from obj2.

Author(s)

Karsten Tabelow tabelow@wias-berlin.de, Joerg Polzehl polzehl@wias-berlin.de

References

J. Polzehl, K. Tabelow (2019). Magnetic Resonance Brain Imaging: Modeling and Data Analysis Using R. Springer, Use R! series. Doi:10.1007/978-3-030-29184-6.