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asegment_sri24 - Segmentation using SRI24 atlas


asegment_sri24 TargetImage OutputImage


Register a target image to a selected channel of the SRI24 human brain atlas, then
reformat one of the atlas label maps to the target image. Note: it is assume that the
target image is skull-stripped, i.e., contains only the brain.


Global Toolkit Options (these are shared by all CMTK tools)
Write list of basic command line options to standard output.

Write complete list of basic and advanced command line options to standard output.

Write list of command line options to standard output in MediaWiki markup.

Write man page source in 'nroff' markup to standard output.

Write command line syntax specification in XML markup (for Slicer integration).

Write toolkit version to standard output.

Write the current command line to standard output.

--verbose-level <integer>
Set verbosity level.

--verbose, -v
Increment verbosity level by 1 (deprecated; supported for backward compatibility).

--threads <integer>
Set maximum number of parallel threads (for POSIX threads and OpenMP).

Main Options
--fast, -f
Fast mode.

The SRI24 channel used for registration to the target image. Supported values:
"spgr", "early-fse", "late-fse", "fa", where the default is "spgr", or use one of the

SPGR (T1-weighted) structural channel [This is the default]

Early-echo (PD-weighted) fast spin echo channel

Late-echo (T2-weighted) fast spin echo channel

--fa Fractional anisotropy channel, derived from diffusion tensor images

The SRI24 label map that is reformatted to the target image. Supported values:
"tzo116plus", "lpba40", "tissue", where the default is "tzo116plus", or use one of
the following:

Extended cortical parcellation template based on Tzourio-Mazoyer AAL 116 region
template. [This is the default]

Template based on the 40 subject LONI Probabilistic Brain Atlas segmentation.

SRI24 maximum likelihood three compartment (GM, WM, CSF) tissue segmentation


Torsten Rohlfing, with contributions from Michael P. Hasak, Greg Jefferis, Calvin R.
Maurer, Daniel B. Russakoff, and Yaroslav Halchenko

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