[MINC-users] Classify

[Jon Erik Ween]

Thanks Andrew see below:

Quoting Andrew Janke <a.janke at gmail.com>:

> > 1) How to optimize the classification so the grey matter is more
> > representative of that seen visually on the 3DT1 (particularly the
> > cortical ribbon)?
>
> To get a better classification I think the first thing you are going
> to have to do is to remove more of the inhomogeneity in the GM/WM
> signal. classify expects the input data to have similar intensities
> for all the WM and GM voxels. Have these images been run through N3?

The steps I used was:

1) nu_correct on the whole 3DT1 volume
2) mincbet -m to generate an initial brain mask
3) Re-run nu_correct on the masked native volume
4) Re-run mincbet -m for an optimized mask
5) subtract the masked subvolume (from 4) from the volume in step 3.

Just running minmask on the output from step 3 gave me a lot of white matter
holes for some reason.

> > 3) Saving the tagfile in "Display" gives you a bit different format
> > (which classify doesn't like)  compared to the tagfile in ../mni/share/
> > classify/ntags_1000_bg.tag
> >
> > Display "save labels .tag":  -82 -109 108 1 1 1
> > /mni/share/classify/ntags_1000_bg.tag:  -82 -109 108 "1"
> >
> > Am I using the wrong function here?
>
> No, I have always just mashed the files about to suit with a text
> editor. The tags from display are more about saving a list of 3D
> points rather than for use with classify.

OK, thanks.

> > 4) Once I get a classified volume (and I have flair lesion and 3DT1
> > lesion in separate masks) how do I calculate volumes? I can't seem to
> > find the functions that do this, though suspect they are in minmath or
> > minccalc somewhere.
>
> Close.
>
>    mincstats -count -mask_binvalue <x>
>
> Is probably what you want.
>
Thanks. I'm supposing I can use this on the masks and the classified volumes
(mincbet mask for total brain volume, flair-mask for hyperintensities, T1 mask
for holes, classified volume for grey, whie and CSF)?

Cheers

Jon