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<div>Ryan,</div>
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<div>Have you tried applying the inverse of the rigid transform defined by landmarks?</div>
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<div>A common mistake is apply the transform that works for aligning landmarks points to an image. They are inverse problems. The transform that is applied to align landmarks is the inverse of the transform that is needed to resample images.</div>
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<div>Hans</div>
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<span style="font-weight:bold">From: </span>Insight-users <<a href="mailto:insight-users-bounces@itk.org">insight-users-bounces@itk.org</a>> on behalf of "Young, Ryan" <<a href="mailto:Ryan.Young@seattlechildrens.org">Ryan.Young@seattlechildrens.org</a>><br>
<span style="font-weight:bold">Date: </span>Thursday, February 11, 2016 at 7:00 PM<br>
<span style="font-weight:bold">To: </span>"<a href="mailto:insight-users@itk.org">insight-users@itk.org</a>" <<a href="mailto:insight-users@itk.org">insight-users@itk.org</a>><br>
<span style="font-weight:bold">Subject: </span>[ITK-users] rigid landmark registartion simpleITK (python)<br>
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<div style="direction: ltr;font-family: Tahoma;color: #000000;font-size: 10pt;">Hello,<br>
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I am trying to rigidly align a group of landmarked samples. I have calculated a rigid transformation matrix. When I apply this to the sample (see code below) is sample is commonly clipped. It seems like the transformation is pushing the sample out out its
physically defined space and the data is lost. How should I set things up to that large translations and rotations do not result in parts of the image being lost.<br>
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affine_center = (0,0,0)<br>
affine_translation =translation<br>
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affine_matrix =T.flatten(order='C') <br>
affine = sitk.AffineTransform(affine_matrix, affine_translation, affine_center)<br>
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imAffine = sitk.Resample(im, imRef, affine,sitk.sitkLinear, sitk.sitkUInt32)<br>
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