I'm not sure how this would happen unless the bounding box or voxel
sizes specified for the spatially normalised images resulted in very
large datasets. The size of the spatially normalised images is
proportional to the total number of voxels. The number of voxels in
an image is computed from the number of voxels along the x, y and z
directions, and each of these is roughly the bounding box maximum
minus the bounding box minimum, all divided by the size of a voxel.
Best regards,
-John
On 14 October 2010 16:25, Jiang, Zhiguo <[log in to unmask]> wrote:
> Hi John:
>
> Really appreciate your advice. But we do get huge file (about 20,000k) after the final normalize (to MNI using the _sn.mat from segment). So we will end up with gigabytes data for one subject.
>
> Do you think we should stick to our old practice (coregister to matchband which shares the same distortion characteristics with EPI session, then use normalize::esti+write ) instead of (coregister to T1 then normalize::write)?
>
> Thanks a lot,
>
> Tony
>
> -----Original Message-----
> From: John Ashburner [mailto:[log in to unmask]]
> Sent: Thursday, October 14, 2010 12:29 AM
> To: Jiang, Zhiguo
> Cc: [log in to unmask]
> Subject: Re: [SPM] Coregister EPI to T1 and Normalise to MNI
>
> There is no need to reslice when you do the coregistration. Just use
> the coregister only option, and this will update the matrices in the
> headers so that SPM can then treat the images as if they are aligned.
> You can see the result of this with CheckReg. Note that the EPI need
> to be not too distorted for this to work. If they are distorted, then
> a rigid body transform will not bring them into good alignment with
> the anatomical scans.
>
> Best regards,
> -John
>
> On 14 October 2010 04:52, Jiang, Zhiguo <[log in to unmask]> wrote:
>> Dear All,
>>
>>
>>
>> Our old preprocessing practice is to coregister EPI to matchband then
>> normalize to MNI. We are trying to take advantage of the T1(MPRAGE). Our
>> plan is to register EPI to T1 then do segment on T1 (to get the _sn.mat)
>> ,from there we normalize the coregsitered EPI to MNI space. But the
>> resulting file is quite large (60 times the size of old practice).
>> Wondering how you guys resolve this issue?
>>
>>
>>
>> Thanks,
>>
>>
>>
>> Tony
>>
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