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Hello Dženan,</div>
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Thanks for your assistance.</div>
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Full code of my example is located here: <a href="https://gist.github.com/jwitos/9abe7124e28ce2e31b6e">https://gist.github.com/jwitos/9abe7124e28ce2e31b6e</a></div>
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I’ve also uploaded the DICOMs I’ve been using (30~MB, 152 .dcms inside) if you want to test them out:
<a href="http://cm-uj.pl/files/cleaned.zip">http://cm-uj.pl/files/cleaned.zip</a></div>
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Best,</div>
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Jan</div>
<p class="airmail_on">On 27 grudnia 2015 at 17:35:24, Dženan Zukić (<a href="mailto:dzenanz@gmail.com">dzenanz@gmail.com</a>) wrote:</p>
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Hi Jan,</div>
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<div class="gmail_default" style="font-family:verdana,sans-serif;font-size:small">
that sounds like some silly simple mistake. If you provided a short compilable example with the accompanying input, somebody will probably be able to point out the problem.</div>
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Regards,</div>
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Dženan</div>
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<div class="gmail_quote">On Sun, Dec 27, 2015 at 10:20 AM, Jan Witowski <span dir="ltr">
<<a href="mailto:jan.witowski@student.uj.edu.pl" target="_blank">jan.witowski@student.uj.edu.pl</a>></span> wrote:<br>
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Hello,</div>
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I am working with CT abdomen images and trying to segmentate the liver (liver itself, vessels and the HCC tumor). I managed to do it using OsiriX which was rather manual segmentation, and now I am working to do the same using more accurate and semi-automatic
algorithms with usage of SimpleITK. I don’t really have much experience with ITK and image manipulation which is why I ask you guys for some help.</div>
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Currently, I want to try the watershed method. I loaded my DICOM series, ran the GradientMagnitude filter and proceeded with MorphologicalWatershed (using arg Level=17, value chosen manually). I got pretty nice output image, I guess:</div>
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<a href="http://jwitowski.com/content/images/2015/12/WSsegmentation-4469-0.jpg" target="_blank">http://jwitowski.com/content/images/2015/12/WSsegmentation-4469-0.jpg</a></div>
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But now, the question is - how do I take that liver out of the image above? My best guess is, I should run a region growing segmentation.</div>
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I tried to do that, but - no matter what parameters I choose - I always get the all-black image as an output. The whole image is black. I tried different thresholds and other starting seeds, but… no result.</div>
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Here is a gist of my segmentation part:</div>
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<a href="https://gist.github.com/jwitos/4b953b3ef873fee3965c" target="_blank">https://gist.github.com/jwitos/4b953b3ef873fee3965c</a></div>
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I would really appreciate any help or tip</div>
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Best,</div>
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Jan Witowski</div>
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Collegium Medicum Jagiellonian University in Krakow</div>
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