[Insight-users] A deformable registration/segmentation question

[Matt McCormick]

Hi Andrew (CC'ing the mailing list -- please remember to reply-to-all),

The tests for the class are also a useful reference.  To see the tests,

ctest -R TimeVarying -N

which yields:


  Test #478: itkTimeVaryingVelocityFieldTransformTest
  Test #479: itkTimeVaryingVelocityFieldIntegrationImageFilterTest
  Test #480: itkTimeVaryingBSplineVelocityFieldTransformTest
  Test #1782: itkTimeVaryingVelocityFieldImageRegistrationTest
  Test #1783: itkTimeVaryingBSplineVelocityFieldImageRegistrationTest

The code for the tests can be found in
Modules/Registration/RegistrationMethodsv4/test/

HTH,
Matt

On Mon, May 6, 2013 at 7:56 PM, Andrew Ho <andrewkennethho at gmail.com> wrote:
> Hey Matt,
> Thanks for the pointer, it sounds like this might be just what I need. Is
> there any documentation, examples, or papers for this method (or class of
> methods) beyond the doxygen generated ones?
>
> Also, are there any limitations on the metric and optimizer which can be
> used with this method? Sorry if these are dumb questions, I'm really new to
> ITK and image registration in general.
>
> Thanks,
> andrew
>
>
> On Mon, May 6, 2013 at 10:28 AM, Matt McCormick <matt.mccormick at kitware.com>
> wrote:
>>
>> Hi Andrew,
>>
>> You may find this class useful:
>>
>>
>> http://www.itk.org/Doxygen/html/classitk_1_1TimeVaryingVelocityFieldImageRegistrationMethodv4.html
>>
>> HTH,
>> Matt
>>
>> On Fri, Apr 26, 2013 at 7:29 PM, Andrew Ho <andrewkennethho at gmail.com>
>> wrote:
>> > Hi there,
>> > I'm wondering if there is a suitable set of tools in ITK for my purpose:
>> >
>> > I have high-resolution 4D CT data of the human upper airway during
>> > swallowing. I'd like segment the upper airway and use it as the moving
>> > boundaries in a physics simulation. The dataset is large, but it's not
>> > too
>> > much to ask to manually segment it (frame by frame). The problem is that
>> > some interpolation is required in time. For this, it seems like a good
>> > approach would be to register sequential time frames and use the
>> > resulting
>> > deformation field to move a mesh. Then interpolation can be performed on
>> > the
>> > deformation field in order to advance the airway structure in time.
>> >
>> > There are a few approaches that I am considering, some of which I
>> > gleaned
>> > from searching the mailing list:
>> >
>> > 1) Perform 3D deformable registration between time frames (using the raw
>> > image data) and acquire deformation fields. Use the deformation field to
>> > move a mesh which is segmented from the first time frame. -- The problem
>> > here is that the registration problem is difficult because of the
>> > rapidly
>> > moving bolus (the fluid being swallowed). There is also poor contrast
>> > between some structures as they close the airway during the sequence.
>> >
>> > 2) Perform 3D manual segmentation on two sequential frames. Generate
>> > meshes
>> > from the segmented surfaces and register these two meshes. Use the
>> > resulting
>> > deformation field to move one mesh to the next time frame. -- The
>> > problem
>> > here (not really a problem) is that I don't know if a mesh to mesh
>> > registration (such as ICP) can be used to generate a deformable field.
>> >
>> > 3) Perform manual segmentation of the airway in frame 1 and use it as
>> > input
>> > to a simplex registration method on frame 2 (suggested here, way back in
>> > 2004:
>> > http://www.itk.org/pipermail/insight-users/2004-November/011080.html)
>> > -- The problem here is that I'm not sure if the segmentation will be
>> > able to
>> > handle the low-contrast areas when closure occurs. Another problem
>> > (again,
>> > not really a problem) is that the files seem to have changed and I'm not
>> > sure if the listed examples are still relevant
>> >
>> > Any suggestions and insight (sorry for that) would be much appreciated!
>> >
>> > Thanks,
>> > andrew
>> >
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