NAME
mincDeconvolve - uses deconvolution to estimate the orientation distribution function (ODF)
SYNOPSIS
mincDeconvolve [options] -DWIs <DWIs.mnc> -mask <calc_mask.mnc> -o <out.mnc>
DESCRIPTION
mincDeconvolve uses the FORECAST (Anderson 2005) algorithm for deconvolution of the diffusion signal. This program allows the reconstruction of multiple fibre orientations per voxel. Your data should include at least 64 non-colinear diffusion directions to succesfully detect multiple fibers. Results of the deconvolution can be viewed with minc3Dvis, using the
-ODFoption.OPTIONS
Usage: mincDeconvolve -DWIs <DWIs.mnc> -mask <calc_mask.mnc> [options] -o <out.mnc> -DWIs: must be single nonzero bvalue (optionally with b=0 as well) series of DWIs in different directions -mask: voxels in which deconvolution will be performed Use these options if you would like to specify a subject-specific response [by default, a population-based average is provided]: -response: file to define the single fiber response -response_voxel: a file in which one voxel is considered the single fibre response function; this voxel and only this voxel is nonzero in response_voxel input -e1 <e1x.mnc> <e1y.mnc> <e1z.mnc> : use this as the single fibre direction (default finds the minimum of the DWI ODF, which might be more error prone than using the fitted tensor). -lambda1 <lambda1.mnc> -lambda2 <lambda2.mnc>: enter the eigenvalues from a previous tensor fit of this data, to be used in the FORECAST deconvolution algorithm (default). Other options: -clobber:overwrite existing <out.mnc> Generic options -help: Print summary of command-line options and abort.EXAMPLES
Apply deconvolution to your diffusion input data (could be the raw images or the ones registered to the T1 antomical from diff_preprocess.)
mincDeconvolve -DWIs infile-reg-with-t1.mnc -mask anat-n3-bet_mask.mnc -o deconvolve.mnc
Ilana LEPPERT
created: 18th September 2009
last modified: 18th September 2009