<div>Hi again!</div>
<div> </div>
<div>Your help is so useful.</div>
<div> </div>
<div>But now I am a bit confused about this you have said...Which of these options is better?</div>
<div> </div>
<div>1) mesh to mesh registration</div>
<div>2) mesh against image (I understand image as a MRI)</div>
<div> </div>
<div>And once I have the mesh of the cortex:</div>
<div> </div>
<div>3) The strategy of registration must be the same of a volume 3D registration? it is first rigid, after affine and at last deformable registration.</div>
<div>4) Can I use the same transform, optimizer of a volume 3D registration? What happens with the metric? I have to be carefull with something else? </div>
<div> </div>
<div>If you have some other advice it will be grateful!</div>
<div> </div>
<div>Thanks!</div>
<div> </div>
<div>MaRC//<br> </div>
<div><span class="gmail_quote">On 10/25/05, <b class="gmail_sendername">Luis Ibanez</b> <<a href="mailto:luis.ibanez@kitware.com">luis.ibanez@kitware.com</a>> wrote:</span>
<blockquote class="gmail_quote" style="PADDING-LEFT: 1ex; MARGIN: 0px 0px 0px 0.8ex; BORDER-LEFT: #ccc 1px solid">Hi Marc,<br><br>Thanks for your detailed and clear questions.<br><br>Here are some comments:<br><br>1) Yes, you can generate Meshes, but first you will need to segment
<br> the brain (or the structures of the brain that you are interested<br> in). For an account of the segmentation methods available in ITK<br> you may want to look at the ITK Software Guide<br><br> <a href="http://www.itk.org/ItkSoftwareGuide.pdf">
http://www.itk.org/ItkSoftwareGuide.pdf</a><br><br> in particular to the "Segmentation" Chapter.<br><br><br>2) Yes, you can conver VTK polydata, or unstructured grids into<br> ITK Meshes, and vice versa.<br>
<br> You will find examples of this in the directories<br><br> InsightApplications/<br> Auxiliary/vtk<br><br> and<br><br> InsightApplications/<br> DeformableModelSimplexMesh
<br><br><br><br><br>3) You may want to try the example code in<br><br> Insight/Examples/Patented/<br> IterativeClosestPoint1.cxx<br> IterativeClosestPoint2.cxx<br>
IterativeClosestPoint3.cxx<br><br><br>For the generic Segmentation problem, you will find<br>many methods intended for brain segmentation.<br><br>In particular statistical classification, and LevelSets.<br><br>You will find validation studies of brain segmentation
<br>in the directory:<br><br><br> InsightApplications/IBSRValidation/<br> IBSRClassification/<br> AtlasSegmentation/<br> FEMAtlasSegmentation/
<br><br><br>4) Doing progressive registration is the way to go.<br> As you pointed out, you want to start with simple<br> Transforms such as Rigid, and then move into<br> Affine, and finally into deformable ones like
<br> BSplines.<br><br><br>5) You may want interesting to consider the registration<br> of a Mesh against an Image. This combination gives<br> you a good tradeof between memory allocation and<br> comptational speed. You may want to use the Mesh
<br> as the Fixed object and the Image as the Moving object.<br><br> The reason is that The Mesh would have less nodes than<br> pixels in the image, and that quering the image for<br> a pixel value is more efficient that searching in the
<br> Mesh for a closest point.<br><br><br><br>If you get something working, you are *strongly* encouraged<br>to post it in the Insight Journal:<br><br><br><a href="http://www.insightsoftwareconsortium.org/InsightJournal/">
http://www.insightsoftwareconsortium.org/InsightJournal/</a><br><br><br><br><br> Regards,<br><br><br> Luis<br><br><br><br><br>------------------<br>Marc Ruiz wrote:<br>> Hi!<br>><br>> My purpose is to register two brain surfaces. Related with this I have
<br>> some questions:<br>><br>> 1) Is it possible to obtain the mesh of the surface of a brain with<br>> itk, using for example a MRI as input image?<br>><br>> 2) Can I take a surface, or better, the mesh of a surface from VTK and
<br>> convert or use it to ITK?<br>><br>> 3) Has ITK a kind of atlas for my goal or do you know one that I could use?<br>><br>> 4) Which classes could be interesting to develope this application?<br>><br>
> Any other idea or problem to comment will be grateful.<br>><br>> On the other hand, I do not know how to quantify the accuracy or the<br>> error when I realize a registration with different steps, it is, first a
<br>> rigid registration to align the brains and later a deformable<br>> registration ( I use ImageRegistration8 and DeformableRegistration7).<br>><br>> Thanks for your help!<br>><br>><br>> ------------------------------------------------------------------------
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