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Hello,
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<div class="">You seem to need a way to interactively explore your program, images and registration setup.</div>
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<div class="">All ITK registration metrics are designed to be minimized. So the correlations are negative if I recall correctly.</div>
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<div class="">You may want to look into Slicer3D (<a href="https://www.slicer.org" class="">https://www.slicer.org</a>) for a image visualizer which is aware of ITK’s image geometry.</div>
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<div class="">You also may want to look into using an interactive programing environment such as Python to better understand the image geometry and the properties of what you are trying to setup.</div>
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<div class="">You may find the SimpleITK Notebooks on Image Registration useful:</div>
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<div class=""><a href="http://insightsoftwareconsortium.github.io/SimpleITK-Notebooks/" class="">http://insightsoftwareconsortium.github.io/SimpleITK-Notebooks/</a></div>
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<div class="">HTH,</div>
<div class="">Brad</div>
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<div class="">On Aug 17, 2016, at 2:52 PM, Andrew Harris <<a href="mailto:aharr8@uwo.ca" class="">aharr8@uwo.ca</a>> wrote:</div>
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<div class="">I am attempting to register two 3D images using the CorrelationImageToImageMetricv4, the LBFGSBOptimizer, and a 3DVersorRigidRegistration. Even if I put the same volumes in to the registration for both the fixed and moving image, I get a very
low value for correlation. One thought I had was I might be setting the origins incorrectly, as previously in the project the origin was defined as the centre of the image cubes and I have attempted to stay with that convention, and I haven’t found an example
in the ITK examples where the origin is set to something other than 0. The other issue might be that the original data is a char array so I had to create a cast filter to change the image to floats, and the origins might be getting confused between the two.
If anyone has any thoughts they would be welcome, I can provide source code if that would be helpful.<br clear="all" class="">
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<p class="">AH<br class="">
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