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mri_watershed - strips skull and other outer non-brain voxels from a normalized T1 volume mri_watershed - strips skull and other outer non-brain voxels from an acquired volume (usually T1).
             
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mri_watershed arg1 -i <arg2> -o <arg3> [<options>] mri_watershed [<options>] [input volume] [brain volume]
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|| [argA] || description || ||[input volume]|| ||
||[output volume]|| ||
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|| -flag1 [arg1] || description ||
|| -flag2 [arg2] || description ||
None
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|| -flag3 [arg3] || description ||
|| -flag4 [arg4] || description ||
 
|| -atlas || use the atlas information to correct the segmentation.|| When the segmented brain is not correct, this option might help you. ||
|| -surf [surfname] || save the BEM surfaces.|| In order to get the surfaces consistent with tkmedit, you have to use the option -useSRAS. ||
|| -useSRAS || use the surface RAS coordinates (not the scanner RAS) for surfaces. || ||
|| -noT1 || don't do T1 analysis. (Useful when running out of memory) || ||
|| -less || shrink the surface || ||
|| -more || expand the surface || ||
|| -wat || use only the watershed algorithm || ||
|| -T1 || specify T1 input volume (T1 grey value = 110) || ||
|| -wat+temp || watershed algo and first template smoothing || ||
|| -first_temp || use only the first template smoothing + local matching || ||
|| -surf_debug || visualize the surfaces onto the output volume || ||
|| -brainsurf [surfname] || save the brain surface || ||
|| -shk_br_surf [int_h surfname] || to save the brain surface shrank inward of int_h mm || ||
|| -s [int_i int_j int_k] || add a seed point || ||
|| -c [int_i int_j int_k] || specify the center of the brain (in voxel unit) || ||
|| -r int_r || specify the radius of the brain (in voxel unit) || ||
|| -t int_threshold || change the threshold in the watershed analyze process || ||
|| -h int_hpf || precize the preflooding height (in percent) || ||
|| -n || not use the watershed analyze process || ||
|| -LABEL || labelize the output volume into scalp, skull, csf, gray and white || ||
|| -man [int_csf int_trn int_gray] || to change the different parameters csf_max, transition_intensity and GM_intensity || ||
|| -mask || mask a volume with the brain mask || ||
|| --help || show usage message || ||
|| --version || show the current version || ||
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|| volume1 || description ||
|| volume2 || description ||
|| [brain volume] || skull stripped brain volume ||
|| [BEM surfaces] || when you specify the option -brainsurf surfname ||
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description Produce the brain volume from T1 volume or the scanned volume.
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mri-watershed foo -i f -o out mri-watershed -atlas T1 brain
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description where T1 is the T1 volume and brain is the output brain volume.
When the cerebellum is cut-off from the brain or getting the left/right asymmetric brain, you should first try this -atlas
option.
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mri-watershed foo -i f -o out -f fvalue mri-watershed T1 brain
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description The same as the first example, but no correction is applied to the intermediate result.

= Bugs =
None
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["othercommand1"], ["othercommand2"] ["mri_normalize"]
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description
description

The "watershed" segmentation algorithm was used to dertermine the intensity values for white matter, grey matter, and CSF.
A force field was then used to fit a spherical surface to the brain. The shape of the surface fit was then evaluated against a previously derived template.

If you used -atlas option, then { The template was used to correct the surface. }

The finely grained sphere was fit to the brain.

(Segonne 2004)
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["References/Lastname###"] ["References/Segonne2004"]
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Report bugs to <analysis-bugs@nmr.mgh.harvard.edu> Report bugs to <freesurfer@nmr.mgh.harvard.edu>
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JaneSmith YasunariTosa

Name

mri_watershed - strips skull and other outer non-brain voxels from an acquired volume (usually T1).

Synopsis

mri_watershed [<options>] [input volume] [brain volume]

Positional Arguments

[input volume]

[output volume]

Required Flagged Arguments

None

Optional Flagged Arguments

-atlas

use the atlas information to correct the segmentation.

When the segmented brain is not correct, this option might help you.

-surf [surfname]

save the BEM surfaces.

In order to get the surfaces consistent with tkmedit, you have to use the option -useSRAS.

-useSRAS

use the surface RAS coordinates (not the scanner RAS) for surfaces.

-noT1

don't do T1 analysis. (Useful when running out of memory)

-less

shrink the surface

-more

expand the surface

-wat

use only the watershed algorithm

-T1

specify T1 input volume (T1 grey value = 110)

-wat+temp

watershed algo and first template smoothing

-first_temp

use only the first template smoothing + local matching

-surf_debug

visualize the surfaces onto the output volume

-brainsurf [surfname]

save the brain surface

-shk_br_surf [int_h surfname]

to save the brain surface shrank inward of int_h mm

-s [int_i int_j int_k]

add a seed point

-c [int_i int_j int_k]

specify the center of the brain (in voxel unit)

-r int_r

specify the radius of the brain (in voxel unit)

-t int_threshold

change the threshold in the watershed analyze process

-h int_hpf

precize the preflooding height (in percent)

-n

not use the watershed analyze process

-LABEL

labelize the output volume into scalp, skull, csf, gray and white

-man [int_csf int_trn int_gray]

to change the different parameters csf_max, transition_intensity and GM_intensity

-mask

mask a volume with the brain mask

--help

show usage message

--version

show the current version

Outputs

[brain volume]

skull stripped brain volume

[BEM surfaces]

when you specify the option -brainsurf surfname

Description

Produce the brain volume from T1 volume or the scanned volume.

Example 1

mri-watershed -atlas T1 brain

where T1 is the T1 volume and brain is the output brain volume. When the cerebellum is cut-off from the brain or getting the left/right asymmetric brain, you should first try this -atlas option.

Example 2

mri-watershed T1 brain

The same as the first example, but no correction is applied to the intermediate result.

Bugs

None

See Also

["mri_normalize"]

Links

FreeSurfer, FsFast

Methods Description

The "watershed" segmentation algorithm was used to dertermine the intensity values for white matter, grey matter, and CSF. 
A force field was then used to fit a spherical surface to the brain. The shape of the surface fit was then evaluated against a previously derived template. 

If you used -atlas option, then { The template was used to correct the surface. }

The finely grained sphere was fit to the brain.

(Segonne 2004) 

References

["References/Segonne2004"]

Reporting Bugs

Report bugs to <freesurfer@nmr.mgh.harvard.edu>

Author/s

YasunariTosa

mri_watershed (last edited 2018-01-04 10:17:45 by MorganFogarty)