<br>HI Abhik,<br><br>You certainly have to write a new Metric <br>class for implementing this.<br><br>The easy option that comes to mind, is to<br>create a metric that internally uses both the Metrics:<br><br>itkMattesMutualInformationImageToImageMetric.h<br>
itkGradientDifferenceImageToImageMetric.h<br><br><br>In your new class, you implement a GetValue()<br>method that calls the GetValue() method of each<br>one of the two metrics and compose them with<br>a linear combination.<br>
<br>Ideally the two internal metrics could be instantiated<br>as member variables, so that you only need to <br>initialize them once.<br><br>You are strongly encouraged to contribute this<br>new class to the Insight Journal. :-)<br>
<br> <a href="http://www.insight-journal.org">http://www.insight-journal.org</a><br><br><br> Regards,<br><br><br> Luis<br><br><br>---------------------------------------------------------------------<br>
<div class="gmail_quote">On Sun, Apr 25, 2010 at 12:29 PM, Abhik Datta <span dir="ltr"><<a href="mailto:findabhik@gmail.com">findabhik@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
Hi All,<div><br></div><div>I am using Mattes Mutual Information registration to register PET / CT data and in my research I am trying to find the effect of adding two terms to my objective function which controls the effect of the gradient matching.</div>
<div><br></div><div>My question is how do I create the new metric class?</div><div><br></div><div>If you can point me to some example code it will be really helpful. The metric itself is very easy to calculate, since I have the implementation for calculating the three terms already. I just need the new metric to be say:</div>
<div><br></div><div>Mattes_MI + x +y instead of just Mattes_MI</div><div><br></div><div>also is there any easier way of doing this? any suggestions will be helpful.</div><div><br></div><div>Thanks & Regards,</div><div>
Abhik.</div>
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