Sulci recognition

[MSh]

Hi

I was wondering if there are any known factors that affect the sulci recognition. For example does accurate white or grey+CSF segmentation play important role? I don't understand why for some subjects recognition works worse than others.

Thanks
MSh

[Jean-Francois Mangin]

Grey/CSF segmentation does not play any role.

The old method based on perceptrons is based on stochastic minimization. Usually we trigger
it a couple of time and keep the best result (very long stuff of course). There is a procedure for that in brainVISA called
parallel recognition I think. This is minimizing the amount of large failure.

But I advise you to use the new recognition procedure which is much more robust for standard brains.

[MSh]

Dear Jean-Francois

Thanks very much for your prompt reply.

Would you advise using "Automatic recognition" (which is default in "T1 pipeline") or "SPAM recognition" for cases where recognition is not very successful?

Thnaks
MSh

[riviere]

Hi,
Yes, the SPAM recognition processes are the newer methods. The T1 pipeline still features the older recognition both for backward compatibility of behaviour, and because the SPAM models need additional data that should be installed in BrainVisa (see the documentation).
Denis