<div dir="ltr">Hi Matt,<div><br></div><div style>Thanks for the help. I am not plotting the histogram however in an image registration setting, but simply using the images themselves, so can't find a way to alter the number of samples. Could you possibly point me in the right direction.</div>
<div style><br></div><div style>Is there also ball park time requirements for me to estimate if my registration process is performing well from a convergence / speed point of view. My images are MRI 200 x 30 x 200 voxels. I haven't reached convergence as of yet and am running for around 2 hours?</div>
<div style><br></div><div style>Thanks for your help</div></div><div class="gmail_extra"><br><br><div class="gmail_quote">On Thu, Dec 5, 2013 at 9:09 PM, Matt McCormick <span dir="ltr"><<a href="mailto:matt.mccormick@kitware.com" target="_blank">matt.mccormick@kitware.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hi Emma,<br>
<div class="im"><br>
> Hi I'm performing some Bspline registration and have looked on the list to<br>
> find this information give regarding the number of samples.<br>
><br>
> The number of samples to take must be enough<br>
> for producing the same "appearance" of the joint histogram<br>
><br>
><br>
> I have plotted the joint histogram but not sure what the same appearance<br>
> means, how do I estimate the number of samples to use from the joint<br>
> histogram?<br>
><br>
<br>
</div>Plotting the histogram is a good first step. Instead of plotting a<br>
single histogram, it may be sufficient to plot multiple histograms<br>
corresponding to different number of samples and look for convergence.<br>
<div class="im"><br>
><br>
> As an aside what drives the number of grid nodes to use, is it simply the<br>
> detail in the image, the amount of motion?<br>
><br>
<br>
</div>It is related to how often the motion is expected to vary, i.e. how<br>
"high frequency" the motion is expected to be. However, avoid too<br>
many grid nodes, at least initially, to prevent the node parameter<br>
optimization from falling into a local minimum.<br>
<br>
Hope this helps,<br>
Matt<br>
</blockquote></div><br></div>