<html><head><meta http-equiv="content-type" content="text/html; charset=utf-8"></head><body dir="auto"><div><span style="-webkit-text-size-adjust: auto;"><a href="http://www.itk.org/Doxygen/html/classitk_1_1LabelImageGaussianInterpolateImageFunction.html">http://www.itk.org/Doxygen/html/classitk_1_1LabelImageGaussianInterpolateImageFunction.html</a></span></div><div style="-webkit-text-size-adjust: auto;"><br>On May 22, 2014, at 4:38 AM, "Gouttard, Sylvain" <<a href="mailto:Sylvain.Gouttard@bioclinica.com">Sylvain.Gouttard@bioclinica.com</a>> wrote:<br><br></div><blockquote type="cite" style="-webkit-text-size-adjust: auto;"><div>
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<p class="MsoNormal">Hi,<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">I am working with a multiple label segmentation image which has at least 3 labels.<o:p></o:p></p>
<p class="MsoNormal">I would be interested in applying a transformation computed from a registration on this multiple label image.<o:p></o:p></p>
<p class="MsoNormal">Even though the transformation is fairly smoothed, when i use the nearest neighbor interpolation, the deformed image is pretty noisy mostly because of the interpolation type i think.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Would there be a solution (algorithm, itk filter, general method…) that would do an interpolation on a multiple label image while keeping the label numbers and performing better than nearest neighbor.
<o:p></o:p></p>
<p class="MsoNormal">Ideally i would like something similar to the sinc interpolation in grey level images.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">For example: when i have a region with label 3 close to a region with label 1, i want to make sure the deformed image will keep these labels 1 and 3 and won't do any average or interpolation creating new labels like label 2 for example.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Thanks for your help,<o:p></o:p></p>
<p class="MsoNormal">Sylvain<o:p></o:p></p>
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