[MINC-users] Automated Segmentation Yet More Questions
Sylvain MILOT
sylvain@bic.mni.mcgill.ca
Tue Jul 6 15:49:04 2004
Hello Paul,
the current mritotal version uses the average_305 model : if you look
in the perl code, you'll find the following variables which are set
with mritotal options -modeldir and -model
$ModelDir = "/usr/local/mni/data/mni_autoreg";
$Model = "average_305";
the icbm model lives in the same directory so use either of the
following invocations:
mritotal -model icbm_avg_152_t1_tal_lin ...
or
do_mritotal -mritotal '-model icbm_avg_152_t1_tal_lin' ...
which is not the same as 'do_mritotal -model icbm_avg_152_t1_tal_lin ...'
!!! since the latter is for resampling, not fitting.
As for question 3, I dont think it will make any difference.
Sylvain
On Tue, 6 Jul 2004, Paul GRAVEL wrote:
> Hello all,
>
> Thank you very much for your feedback.
> It does however raise a few questions.
> (Please see below for previous replies to previous questions).
>
> 1 - Since ANIMAL uses the ICBM152 model for more robust linear
> registrations, does this mean that "mritotal" uses
> the ICBM152 model by default as well, or should I use the
> "-model icbm_avg_152_t1_tal_lin"?
>
> e.g. mritotal -model icbm_avg_152_t1_tal_lin $arg1'_mri.mnc' $arg1'_mri_stx_lin.xfm'
>
> 2 - If the "-model" switch needs to be used, is the
> "icbm_avg_152_t1_tal_lin" file the correct option to use
> for the ICBM152 model?
>
> 3 - After segmentation, in order to remove voxels in the skull,
> should I use a different mask than "average_305_mask.mnc"?
>
> Once again, I thank you.
>
> Best Regards,
>
> Paul
>
> On Mon, 21 Jun 2004, D. Louis Collins wrote:
>
> > Paul,
> >
> > The procedure described on my web site is still valid, however, many of
> > the programs have been updated and yield better results now.
> >
> > Answers are below.
> >
> > -Louis
> >
> >
> > On Jun 21, 2004, at 11:07 AM, Paul GRAVEL wrote:
> >
> > > Hi All,
> > >
> > > I am not sure if this is the appropriate mailing list to send these
> > > questions(bottom of e-mail) to, but I will ask them anyway. Please
> > > let me
> > > know if I should send them to another mailing list.
> > >
> > > I have 42 subjects that I needed to segment into several ROI's.
> > > I used the procedure displayed on Dr. Louis Collins Web Page
> > > (http://www.bic.mni.mcgill.ca/users/louis/pet_segment)
> > >
> > > The procedure is as followed:
> > >
> > > Step 1: mritotal $arg1'_mri.mnc' $arg1'_mri_stx_lin.xfm'
> > >
> > > Step 2: nu_correct $arg1'_mri.mnc' $arg1'_mri_nuc.mnc'
> > >
> > > Step 3: mritotal -nonlinear $arg1'_mri_nuc.mnc' -transformation
> > > $arg1'_mri_stx_lin.xfm' $arg1'_mri_stx_nonlin.xfm'
> > >
> > > Step 4a: mincresample -like
> > > /avgbrain/brain/images/icbm_template_1.00mm.mnc
> > > $arg1'_mri_nuc.mnc' -transformation $arg1'_mri_stx_lin.xfm'
> > > $arg1'_mri_stx_nuc.mnc'
> > >
> > > Step 4b: classify_clean $arg1'_mri_stx_nuc.mnc'
> > > $arg1'_mri_stx_classes.mnc'
> > >
> > > Step 5: stx_segment $arg1'_mri_stx_nonlin.xfm' $arg1'_mri_stx_lin.xfm'
> > > $arg1'_mri_stx_classes.mnc' $arg1'_mri_stx_labels.mnc'
> > >
> > >
> > > My questions are as followed:
> > >
> > > 1 - Is this still the best procedure to do segmentation?
> >
> > pretty much. ANIMAL now uses the ICBM152 model for more robust linear
> > registrations.
> >
> > > 2 - Is step 2(nu_correct) based on the N3 Algorithm, if not which
> > > algorithm is it based on?
> >
> > this is based on N3, the method of John Sled.
> >
> > > 3 - Is step 4b(classify_clean) based on the INSECT (Intensity
> > > Normalized
> > > Stereotaxic Environment for the Classification of Tissue) Algorithm, if
> > > not which algorithm is it based on?
> >
> > classify_clean is a perl script that uses both bayesian and artificial
> > neural nets for classification and is based on INSECT.
> >
> > > 4 - Is step 5(stx_segment) based on the ANIMAL (Automatic Nonlinear
> > > Imaging Matching and Anatomical Labelling) Algorithm, if not which
> > > algorithm is it based on?
> >
> > step 5, stx_segment, takes the output of the linear and non-linear
> > registrations and combines it with the classified data to achieve a
> > segmentation. The entire procedure, registrations+classifications is
> > ANIMAL.
> >
> > Hope this helps,
> >
> > -L
> >
> >
> > >
> > > I thank you very much in advance.
> > >
> > > Best Regards,
> > >
> > > Paul
> > > ______________________________
> > >
> > > Paul Gravel
> > > Neurobiological Psychiatry Unit
> > > McGill University
> > > 1033 Pine Avenue West
> > > Montreal, Quebec, Canada, H3A 1A1
> > > Phone: (514) 398-7301
> > > Fax: (514) 398-4866
> > >
> > >
> > >
> > >
> > > _______________________________________________
> > > MINC-users@bic.mni.mcgill.ca
> > > http://www.bic.mni.mcgill.ca/mailman/listinfo/minc-users
> >
>
> ______________________________
>
> Paul Gravel
> Neurobiological Psychiatry Unit
> McGill University
> 1033 Pine Avenue West
> Montreal, Quebec, Canada, H3A 1A1
> Phone: (514) 398-7301
> Fax: (514) 398-4866
>
>
> _______________________________________________
> MINC-users@bic.mni.mcgill.ca
> http://www.bic.mni.mcgill.ca/mailman/listinfo/minc-users
>
---
Sylvain Milot (sylvain@bic.mni.mcgill.ca)
(trinity@bic.mni.mcgill.ca)
Brain Imaging Centre
Montreal Neurological Institute
Webster 2B, Room 208
Montreal, Qc., Canada, H3A 2B4
Phone : (514) 398-4965, 1996 Fax: 8948
Mobile : (514) 712-1768
Office : 527 Pine, room 204