<div dir="ltr">Dear Dr.Susumu and colleagues <div>I use DtiStudio, ROIeditor and Diffeomap. I have got small problem. Diffeomap give me 160 region or 180.</div><div> I need 180 regions of label list, some time. Have you got it? </div>
<div>Thank you very much for your help. </div><div>Best regards</div><div><br></div><div>Niyazi Acer, PhD</div><div>Erciyes University, School of medicine, </div><div>Anatomy department, Kayseri-Turkey. </div></div><div class="gmail_extra">
<br><br><div class="gmail_quote">On Thu, Sep 12, 2013 at 4:20 AM, Susumu Mori <span dir="ltr"><<a href="mailto:smoriw@gmail.com" target="_blank">smoriw@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div dir="ltr"><br><div class="gmail_extra"><br><br><div class="gmail_quote"><div class="im">On Mon, Sep 9, 2013 at 1:39 PM, Dorian P. <span dir="ltr"><<a href="mailto:alb.net@gmail.com" target="_blank">alb.net@gmail.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Dear developers,<div><br></div><div>In a recent paper from Ceritoglu et al. "Computational analysis of LDDMM for brain mapping" it seems like sequential thresholds in LDDMM can speed the calculation process. Is this the case, does adding three thresholds (0.05 0.01 0.004) be faster than adding only one (0.004)?</div>
</div></blockquote><div><br></div></div><div>I forwarded this this question to Can.</div><div class="im"><div> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">
<div><br></div><div>Second, my understanding is that LDDMM is better for DTI processing than other normalization algorithms (i.e. the one SPM uses). Is there any empiric comparison of this, is LDDMM better (at single or dual channels)?</div>
</div></blockquote><div><br></div></div><div>Well, if you ask this question, I would say LDDMM is better, but if you ask the same question to Dr. Ashburner, you may get a different answer. I believe both LDDMM and Dartel/SPM share a similar deffeomorphic transformation theory. So, I assume the similar performance. Both should be better than pre-Dartel transformation methods SPM was offering, but it's just my guess. There are some unique functions in our LDDMM such as cascading elasticity controls and multi-contrast simultaneous registration, both have significant impact on accuracy, but there may be similar functions in Dartel/SPM by now</div>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">
<div><br></div><div>Thank you.</div></div>
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