Hi, all
Bruce has suggested that we can directly give recon-all dcm file as input.
However, I have done recon-all with mgz file as input. Is that input file
OK?
For example, sub1 has 128 dcm files, 001~128, I just ran a syntax:
mri_convert 001 sub1.mgz
then the computer read 128 dcm files and convert them into sub1.mgz, then I
ran recon-all with "sub1.mgz" as input file
The version I used was freesurfer-Linux-centos4-stable-pub-v4.5.0
Besides, I have checked the aseg.stats and lh/rh.aparc.stats generated from
different input files(dcm or mgz) in one subject, and find that they are
completely the same.
It must be a very stupid question, however, I need some confirmation. Too
much Thanks!
Jin

2010/5/4 Bruce Fischl <fis...@nmr.mgh.harvard.edu>

> if the directions are labeled properly then you aer probably ok. In general
> you are better off just giving recon-all the dicom files as input and not
> doing any conversions beforehand.
>
> cheers
> Bruce
>
> On Tue, 4 May 2010, chenchunhuichina wrote:
>
>  Hello FreeSurfer users,
>>
>> I may be asking a stupid question but it really troubled me a while.
>>
>> I converted dicom files to nift using dcm2niigui (MRIcron). In fslview, it
>> displayed in RAS coordinates, but template of FSL are in LAS coordinates.
>> Should I filp L-R before doing any further analysis?
>> Besides, my structrual imagews were scanned in sagittal view, and after
>>  dcm2niigui transforation, it's in PIL coordinates in fslview. Should I
>> reorient the image to LAS coordinates too?
>> But the letters L R I S A P are labled correctly (at least A-P and I-S are
>> correct), which means FSL can read in orientation information correctly. So
>> I am confused whether I should reorient my data or not.
>> I then processed strucutre images with Freesurfer, and the results from
>> reoriented and not-reoriented images are different, so which one is correct?
>>
>> Any help is appreciated,
>> Thanks!
>> --
>>
>> Chunhui Chen
>>
>>
>> 2010-05-04
>>
>>
>>
>> Chunhui Chen
>> _________________
>>
>> Institute of Cognitive Neuroscience and Learning
>> Beijing Normal University
>> Beijing, China 100875
>>
>
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