[Insight-users] demons deformable filter
Corinne Mattmann
mattmaco at ee.ethz.ch
Wed, 14 Jan 2004 10:07:28 -0700
Hi Luis,
Thanks very much for your answer. At the moment there's just one thing I
don't understand:
In itkDemonsRegistrationFunction I have the variable "index" which
contains the position in the fixed image I am looking at that moment. To
get the intensity value of the moving image at the surrounding points I
have to know which points of the original moving image are mapped to
that surrounding points.
In point B) you wrote that I just have to take those surrounding points
and map them through the deformation field. And here is what I don't
understand: In the description of the DemonsRegistrationFilter I've read
that the "deformation field maps the moving image onto the fixed image".
If I understand this statement correctly, this means that the
deformation field contains a vector in each point, telling me where the
intensity value of the moving image is positioned after the
registration.
Therefore to get the positions in the moving image of the mentioned
surrounding points I would somehow have to go backwards through the
deformation field. Is this right or do I misunderstand something? And if
I understand it right how can I then get the mapped moving values
without calculating tho whole image in InitializeIteration()?
Thanks very much,
Corinne
-----Original Message-----
From: Luis Ibanez [mailto:luis.ibanez at kitware.com]
Sent: Tuesday, January 13, 2004 4:37 PM
To: Corinne Mattmann
Cc: insight-users at itk.org
Subject: Re: [Insight-users] demons deformable filter
Hi Corinne,
You probably want to start by creating new classes
itkDemons5RegistrationFunction
itkDemons5RegistrationFilter
You can simply copy & rename them from the
currently existing DemonsRegistration classes,
and then do the following modifications on them:
A) itk::Demons5RegistrationFunction still derives
from itk::PDEDeformableRegistrationFunction so
it has access to the protected member variable:
m_DeformationField
This variable is not set by default, so you have
to modify the itkDemons5RegistrationFunction and
add in the InitializeIteration() method the following
lines
> // update variables in the equation object
> DemonsRegistrationFunctionType *f =
> dynamic_cast<DemonsRegistrationFunctionType *>
> (this->GetDifferenceFunction().GetPointer());
>
> if ( !f )
> {
> itkExceptionMacro(<<"FiniteDifferenceFunction not of type
DemonsRegistrationFunctionType");
> }
>
> f->SetDeformationField( this->GetDeformationField() );
>
This will set the pointer on the function.
Make sure that this new lines of code are BEFORE
the line invoking
Superclass::InitializeIteration();
B) Now, you can modify itkDemons5RegistrationFunction
for computing an estimation of the gradient by using
finite differences. For this you take the point on
the fixed image coordinate frame where you want to
compute the gradient of the deformed moving image.
From this point you generate 2 x N points
(N = image dimension). Those points are computed
as P +- delta[i].
For example in 2D you will get points like:
Py+
|
|
Px- ----P----Px+
|
|
Py-
Then you take those points and map them through
the deformation field, so you will get points
Qx+,Qx-,Qy+,Qy- (and so on if you are in N>2).
With these points you can use the interpolator
and get intensity values from the moving image
and finally compute the gradient vector as
Gx = (Qx+ - Qx-) / (2.0 * xspacing)
Gy = (Qy+ - Qy-) / (2.0 * yspacing)
(and so on if you are in N > 2).
This may not be very elegant but should give you
a reasonable estimation of the gradient of the
deformed moving image.
BTW If you get it working and you are willing to
contribute this code back to ITK we will be happy
to include it in the toolkit. Probably with better
names for the files.
Regards,
Luis
--------------------------
Corinne Mattmann wrote:
> Hi,
>
> I am using the demons deformable filter but as I have images with just
> one "material" - therefore basically black-white-images with smoothed
> transitions - the registration is not perfect. In fact, the quality of
> the registration depends on the similarity of the two initial images.
> That's why I would like to try another demons-formula taken out of
> Jean-Philippe Thirion's paper "Fast Non-Rigid Matching of 3D Medical
> Images" (formula 5). For that formula you need to calculate the
> gradient of the reconstructed moving image at each iteration. Can you
> tell me how I can get to this gradient in the function
> ComputeUpdate(...) in itkDemonsRegistrationFunction.txx?
>
> Thanks very much,
> Corinne
>
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