Hi - I think you need to start by looking at each 'timepoint' in all_FA to see how the individual registrations look - for example, does it look like bad subjects have gross misalignments (i.e. from the initial affine registration with FLIRT) or problems in the nonlinear registration (FNIRT).

Cheers.

On 30 Nov 2010, at 16:37, Sara Bergman wrote:

Thanks for your suggestion. We do suspect that the problem lies in the registration of the images. We have used a bet threshold of .4 in some cases and .25 in others, and we have made sure that the images after bet look ok.

Can you please elaborate on how we should go about fixing our poor registrations and how to identify which one's need fixing? Thanks for you help!

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Stephen M. Smith, Professor of Biomedical Engineering
Associate Director, Oxford University FMRIB Centre

FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK
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