[MINC-users] Classify

[Andrew Janke]

Hi Jon,

> 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?

> 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.

> 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.


--
Andrew Janke
(a.janke at gmail.com || http://a.janke.googlepages.com/)
Canberra->Australia    +61 (402) 700 883