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Dear Christian,
   
  Thank you.
   
  It is introduced that betfunc uses a -f 0.3 for 4D fmri data while I found bet in Melodic uses a -f 0.4. Bet in melodic cut off the most top slice of my data but betfunc didn't. I think it is better for my data to use betfunc first then pass the mask made to melodic explicitly, as you said.  
   
  Regards,
   
  wei

Christian Beckmann <[log in to unmask]> 写道：
  Hi

melodic uses a different approach to robustifying bet for 4D data. In 
betfund, the inital mask is generated from the first image and then 
dilated by 1 voxel in x,y and z before masking all volumes by this 
new dilated mask. In melodic the bet outline is found by running bet 
on the mean image across time. I have not evaluated the differences 
explicitly but guess that they are small. Note that you can always 
pass a mask to melodic explicitly by using the -m option
cheers
christian



On 23 May 2007, at 15:49, pengxu wei wrote:

> Dear list,
>
> I have read some message in the archive but no answer available. 
> betfunc is better than routine bet for 4D fmri data, so whether bet 
> in Melodic is betfunc(when using GUI or command line), or just 
> routine bet?
>
> Regards,
>
> wei
>
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____
Christian F. Beckmann
University Research Lecturer
Oxford University Centre for Functional MRI of the Brain (FMRIB)
John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK.
[log in to unmask] http://www.fmrib.ox.ac.uk/~beckmann
tel: +44 1865 222551 fax: +44 1865 222717


       
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