"LL" stand for LogLikelihood ? ;-)On Tue, Jun 25, 2013 at 10:57 PM, Bruce Fischl <fischl@nmr.mgh.harvard.edu> wrote:
for the aseg it's these lines:
.
.
.
pass 1: 89966 changed. image ll: -2.224, PF=1.000
pass 2: 15019 changed. image ll: -2.221, PF=1.000
pass 3: 5116 changed.
pass 4: 2124 changed.
writing labeled volume to aseg.auto_noCCseg.mgz...
although I guess I only compute it for the first couple of iterations of ICM
cheers
Bruce
On Tue, 25 Jun 2013, Dov Sadan wrote:
This ?Computing Initial Surface Statistics
-face loglikelihood: -8.0702 (-4.0351)
-vertex loglikelihood: -6.6450 (-3.3225)
-normal dot loglikelihood: -3.4961 (-3.4961)
-quad curv loglikelihood: -6.1619 (-3.0810)
Total Loglikelihood : -24.3732
On Tue, Jun 25, 2013 at 10:34 PM, Bruce Fischl <fischl@nmr.mgh.harvard.edu>
wrote:
No, not that. That is the density reestimation. Later on it
should write out the log posterior
On Jun 25, 2013, at 3:32 PM, Dov Sadan <dov.sadan.19@gmail.com> wrote:
Dear Buche,
Thank you very much for your quick reply.
Do you mean those lines: (from recon-all. log)
==================
.
.
.
gca peak = 0.27536 (62)
mri peak = 0.11940 (97)
Right_Hippocampus (53): linear fit = 1.55 x + 0.0 (325 voxels,
overlap=0.000)
Right_Hippocampus (53): linear fit = 1.55 x + 0.0 (325 voxels,
peak = 96), gca=96.1
.
.
===================
If this is what you meant, can you shed some light on this log.
What "gca peak" / "mri peak" means? And what the number
insight the parentheses represent ?
Thanks in advance,
Assaf
On Tue, Jun 25, 2013 at 9:49 PM, Bruce Fischl
<fischl@nmr.mgh.harvard.edu> wrote:
Hi Dov
I think it writes out the log posterior at each
iteration of the aseg (mri_ca_label)
cheers
Bruce
On Tue, 25 Jun 2013, Dov Sadan wrote:
Hi there,
I'm wondering if there's any parameter
which can assess the correctness of
the freesurfer's segmentation (
the aparc.a2009s+aseg.mgz file).
--> Assuming the freesurfer's algorithm
fitting/minimizing an objective
function, right ? If so, where I can
find the value of this
fitted function ? (or RMS value ?)
Thanks in advance,
Dov
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