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<P>Hello,</P>
<P>Can I use watershed example (from ITK1.8\Examples\WatershedSegmentation1.cxx) with Brain MRIs (Raw format)? When I try to use Watershed example on Brain MRI with tumour, with following parameters range- </P>
<P>Conductance Term -> 1-4, No. of Iterations - 3 - 10, Threshold (%) - 0.0 - 0.3, Level Of Watershed 0.01 - 0.05,<BR>Principle Componenet Analysys - On. I am not sure if I need to use Principle Componenet Analysys.</P>
<P>I get following error: ------></P>
<P>itk::ExceptionObject (0104F288)<BR>Location: "Unknown"<BR>File: C:\ITK_1.8\InsightToolkit-1.8.0\Code\Algorithms\itkWatershedSegmentTreeGen<BR>erator.txx<BR>Line: 436<BR>Description: itk::ERROR: itk::watershed::SegmentTreeGenerator::MergeSegments:: A<BR>n unexpected and fatal error has occurred. This is probably the result of overth<BR>resholding of the input image.</P>
<P>Do you have any suggestions? I have attached the image. I give .mhd file as an input to that example program.</P>
<P>Thanks.</P></DIV><BR><BR><B><I>Luis Ibanez <luis.ibanez@kitware.com></I></B> wrote:
<BLOCKQUOTE class=replbq style="PADDING-LEFT: 5px; MARGIN-LEFT: 5px; BORDER-LEFT: #1010ff 2px solid"><BR>Hi Neha,<BR><BR>We don't have examples of these two filters are this point.<BR>This issue has been entered as a feature request in the<BR>bug tracker. Bug # 1309:<BR><BR>http://www.itk.org/Bug/bug.php?op=show&bugid=1309&pos=0<BR><BR>----<BR><BR>Regarding your question about pre-post contrast:<BR><BR>Yes, it is worth to give it a try at subtracting these two<BR>images. You will recognize if registration is needed if<BR>you see a lot of borders in the structures after the<BR>subtraction.<BR><BR>It is quite likely that you will need deformable registration<BR>since the image acquisition process for Breast under MRI does<BR>not restrict patient movement.<BR><BR>The deformable registration methods in ITK have been previously<BR>applied to registration of MRI Breast images. In particular the<BR>combination of BSplineDeformableTransform and MutualInformation.<BR><BR>Look for
example at the Tutorials<BR><BR>http://www.itk.org/HTML/Tutorials.htm<BR><BR>In particular the session on Registration by Dr. Lydia Ng.<BR>http://www.itk.org/CourseWare/Training/RegistrationMethodsOverview.pdf<BR><BR>You will find examples on deformable registration of pre/post<BR>constrast MRI Breast images in page 64.<BR><BR><BR><BR>Regards,<BR><BR><BR><BR>Luis<BR><BR><BR><BR>--------------------------<BR>neha k wrote:<BR><BR>> Hello Luis,<BR>> Thanks for your reply. Is there any example on <BR>> GrayScaleFillHoleImageFiler or GrayScaleGrindPeakImageFilter? What <BR>> book can I refer to understand these filters?<BR>> <BR>> Also, can you please let me know what you mean by "fine tune the structuring<BR>> element for matching the relative size of calcifications in image". <BR>> <BR>> Since I need pair of breast MRIs (Which unfortunately are not avilable <BR>> to me) I checked mypacs.net, where I found one set of images GRE-images <BR>> at following
link - <BR>> http://www.mypacs.net/cgi-bin/repos/mpv3_repo/wrm/repo-view.pl?cx_subject=28078&cx_image_only_mode=off&cx_repo=mpv3_repo&cx_from_folder <BR>> <HTTP: repo-view.pl?cx_subject="28078&cx_image_only_mode=off&cx_repo=mpv3_repo&cx_from_folder" wrm mpv3_repo repos cgi-bin www.mypacs.net>=<BR>> Fil. 9,10 and 11. Does it make sense to use these 2 images, <BR>> subtracting them and applying Watershed on the result. If so, how can I <BR>> decide by checking these images if that needs deformable registration?<BR>> Any input on this is most appreciated. <BR>> Thanks,<BR>> Neha<BR>> <BR>> */Luis Ibanez <LUIS.IBANEZ@KITWARE.COM>/* wrote:<BR>> <BR>> <BR>> HI Neha,<BR>> <BR>> You can find Breat images at<BR>> <BR>> www.mypacs.net<BR>> <BR>> you can create an account for free and<BR>> download real datasets.<BR>> <BR>> Look for the title "Shared Cases" and<BR>> click in "Breast".<BR>> <BR>>
--<BR>> <BR>> You may want try the advanced Mathematical Morphology<BR>> methods such as: FillHole and GrindPeak.<BR>> <BR>> http://www.itk.org/Insight/Doxygen/html/classitk_1_1GrayscaleFillholeImageFilter.html<BR>> http://www.itk.org/Insight/Doxygen/html/classitk_1_1GrayscaleGrindPeakImageFilter.html<BR>> <BR>> Taking an input imag, applying one of these filter and<BR>> then subtracting from the original may enhance spiculations<BR>> and calcificaitions. You will have to fine tune the structuring<BR>> element for matching the relative size of calcifications in your<BR>> image.<BR>> <BR>> <BR>> Regards,<BR>> <BR>> <BR>> Luis<BR>> <BR>> ----------------------------<BR>> neha k wrote:<BR>> <BR>> > Hello All,<BR>> ><BR>> > I am working on Breast Image Segmention for deleneating lesions,<BR>> ducts<BR>> > and fat tissues. Problem is that I don't have Breast Images with<BR>> > contrast
agent used. Hence I can't have pre and post contrast agent<BR>> > to subtract them and locate tumour etc. What will be the best way to<BR>> > segment such breast images (in RAW format). I am currently trying to<BR>> > use Watershed segmentation and not getting any good results with it.<BR>> > It causes lot of oversegmentation. I have not used Level Set Seg.<BR>> > method yet.<BR>> > Any input is appreciated.<BR>> ><BR>> > Thanks,<BR>> > Neha<BR>> ><BR>> ><BR>> <BR>> <BR>> <BR>> ------------------------------------------------------------------------<BR>> Do you Yahoo!?<BR>> Yahoo! Mail – CNET Editors' Choice 2004. Tell them what you think <BR>> <HTTP: 4852-9236_7-30980704.html?part="editchoice" Yahoo_Mail reviews.cnet.com>. <BR>> <BR><BR><BR><BR><BR></BLOCKQUOTE></DIV><p>__________________________________________________<br>Do You Yahoo!?<br>Tired of spam? Yahoo! Mail has the best spam
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