Print

Print
Thanks for your reply.
OK, i got the idea that if the registration picture looks fine, i shouldn't need to worry a bout that warning.
but i am really curious if it's true that in version 4.1.4 they just hide those warnings, and in 4.1.5 they just show that? that make sense when i was using the same design (no change at all), but get different log files in those warnings, but all others are the same.
 just want to make sure.
thanks,
-Qinghua

Date: Fri, 23 Apr 2010 21:05:59 +0200
From: [log in to unmask]
Subject: Re: [FSL] Feat Registration Question
To: [log in to unmask]

Dear Qinghua,


I have a question regarding the registration part in Feat.
previously, when my FSL version was 4.1.4, the registration runs smoothly (without warning or error).

but, after i installed new version of FSL (4.1.5), i found that the registration for my new subject got some warnings. and then, i just re-run the same subject i have already done to check out if this is because of the subject, but again i got these warnings, quote  from the log file:
"Setting subsampling
Setting reg mode
Setting lambda
SpMat::SolveForx: Warning requested tolerence not obtained.
Requested tolerance was 0.001, and achieved tolerance was 0.851883
This may or may not be a problem in your application, but you should look into it
SpMat::SolveForx: Warning requested tolerence not obtained.
Requested tolerance was 0.001, and achieved tolerance w!
 as 0.160804
This may or may not be a problem in your application, b
ut you should look in!
 to it
this is an error message from fnirt. For every iteration fnirt solves a large system of equations numerically. That solution can be more or less stable (the coefficient matrix can be close to singular). When it encounters a close to singular coefficient matrix it prints these error messages.

However, there is an inherent "stabiliser" built into fnirt so that for the next iteration it will make sure the matrix is better conditioned. Hence these warnings are usually not a problem when you just see a couple of them and the registered images still look good.

I cannot say why it appears now on the same data where before it didn't, but even very small changes in the code (and subsequently in this matrix) can have effect on the conditioning of the matrix.

In conclusion, if the registered images look good this is nothing to worry about.
!

Good Luck Jesper


Hotmail: Trusted email with powerful SPAM protection. Sign up now.