[Insight-users] registration using rotation + translation

Fri Dec 3 12:07:44 EST 2010

Of the potential problems mentioned, the most obvious is getting the data
oriented roughly, so I'm trying to do that first.  I'm using
ResampleImageFilter4.cxx, modified for 3D rotation.  Input and output is
mhd, unsigned shorts.

When I rotate the volume by any amount, there is no visible difference.  I
tried 0, 1, 10, 45, 89, and 90 deg.  What am I doing wrong?

When a volume is rotated, the dimensions of the volume in the output mhd
file should account for it, right?  So rotating 45 deg should increase one
of the dimensions.

#include "itkImage.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkResampleImageFilter.h"
#include "itkLinearInterpolateImageFunction.h"

#include "itkAffineTransform.h"

int main( int argc, char * argv[] )
{
  if( argc < 4 )
    {
    std::cerr << "Usage: " << std::endl;
    std::cerr << argv[0] << "  inputImageFile  outputImageFile  degrees" <<
std::endl;
    return EXIT_FAILURE;
    }

  const     unsigned int   Dimension = 3;
  typedef   unsigned short  InputPixelType;
  typedef   unsigned short  OutputPixelType;

  typedef itk::Image< InputPixelType,  Dimension >   InputImageType;
  typedef itk::Image< OutputPixelType, Dimension >   OutputImageType;

  typedef itk::ImageFileReader< InputImageType  >  ReaderType;
  typedef itk::ImageFileWriter< OutputImageType >  WriterType;

  ReaderType::Pointer reader = ReaderType::New();
  WriterType::Pointer writer = WriterType::New();

  reader->SetFileName( argv[1] );
  writer->SetFileName( argv[2] );

  const double angleInDegrees = atof( argv[3] );

  typedef itk::ResampleImageFilter<
                  InputImageType, OutputImageType >  FilterType;

  FilterType::Pointer filter = FilterType::New();

  typedef itk::AffineTransform< double, Dimension >  TransformType;
  TransformType::Pointer transform = TransformType::New();

  typedef itk::LinearInterpolateImageFunction<
                       InputImageType, double >  InterpolatorType;
  InterpolatorType::Pointer interpolator = InterpolatorType::New();

  filter->SetInterpolator( interpolator );

  filter->SetDefaultPixelValue( 100 );

  reader->Update();

  const InputImageType * inputImage = reader->GetOutput();

  const InputImageType::SpacingType & spacing = inputImage->GetSpacing();
  const InputImageType::PointType & origin  = inputImage->GetOrigin();
  InputImageType::SizeType size =
      inputImage->GetLargestPossibleRegion().GetSize();

  filter->SetOutputOrigin( origin );
  filter->SetOutputSpacing( spacing );
  filter->SetOutputDirection( inputImage->GetDirection() );
  filter->SetSize( size );

  filter->SetInput( reader->GetOutput() );
  writer->SetInput( filter->GetOutput() );

  TransformType::OutputVectorType translation1;

  const double imageCenterX = origin[0] + spacing[0] * size[0] / 2.0;
  const double imageCenterY = origin[1] + spacing[1] * size[1] / 2.0;
  const double imageCenterZ = origin[2] + spacing[2] * size[2] / 2.0;

  translation1[0] =   -imageCenterX;
  translation1[1] =   -imageCenterY;
  translation1[2] =   -imageCenterZ;
  transform->Translate( translation1 );

  std::cout << "imageCenterX = " << imageCenterX << std::endl;
  std::cout << "imageCenterY = " << imageCenterY << std::endl;
  std::cout << "imageCenterZ = " << imageCenterZ << std::endl;

  const double degreesToRadians = vcl_atan(1.0) / 45.0;
  const double angle = angleInDegrees * degreesToRadians;
  transform->Rotate3D( -angle, false );

  TransformType::OutputVectorType translation2;
  translation2[0] =   imageCenterX;
  translation2[1] =   imageCenterY;
  translation2[2] =   imageCenterZ;
  transform->Translate( translation2, false );
  filter->SetTransform( transform );

  try
    {
    writer->Update();
    }
  catch( itk::ExceptionObject & excep )
    {
    std::cerr << "Exception caught !" << std::endl;
    std::cerr << excep << std::endl;
    }

  return EXIT_SUCCESS;
}

On Tue, Nov 30, 2010 at 9:29 PM, Luis Ibanez <luis.ibanez at kitware.com>wrote:

> Hi Kevin
>
> On Tue, Nov 30, 2010 at 1:23 PM, Kevin Neff <kevin.l.neff at gmail.com>
> wrote:
> >
> > Thanks, Dan.  I used the example ImageRegistration8.cxx with my data.
> >
> > First, it's terribly slow.  Is there anything I can do to speed it up?
>
>
> 1)  How long it took ?
>
> 2)  How many cores do you have ?
>
> 3) What version of ITK are you using ?
>
> 4) Make sure that you compile it for Release mode.
>     (that easily makes a difference of 10x with respect to Debug mode).
>
>
> > my limited experience, applying a threshold first and skipping rotation
> of
> > voxels below the threshold helped.  Or could I pre-compute isotropic
> voxels
> > and skip the interpolation that follows image rotation and just
> interpolate
> > the final solution?  Any suggestion is welcome!
> >
>
> You could also use a Mask,
> See example:
>
> ITK/Examples/Registration/ImageRegistration12.cxx
>
>
> > Second, after 200 iterations,  the output does not appear correct.  I ran
> it
> > with data that had the dimensions 13888x560x48 and 1388x560x53 but the
> > output had the dimensions 13888x560x48.  The volumes were of the shell of
> a
> > large object, rotated 90 deg, so I'm sure the dimension of the output
> should
> > have been much larger---something like 1388x1000x100.
>
> a) 90 degrees is beyond the capture radio of any registration method.
>    You must initialize the Transform to account for most of that rotation.
>    In practice you shouldn't expect the optimization process to correct
>    for more than 20 to 30 degrees of rotation.
>
> b) Is that rotation along the long axis of your image ? or perpendicular to
> it ?
>    A screen shot of your image will be very helpful...
>
> c) You should carefully control the parameter scales to make sure that
>    you account for the proportion of radians units (used for rotation) to
>    millimeters used for translation.
>
> d) What is the pixel spacing of your images ?
>
>
> >
> > KLN
> >
> >
> >
> >
> >
> > On Sun, Nov 21, 2010 at 7:55 AM, Dan Mueller <dan.muel at gmail.com> wrote:
> >>
> >> Hi Kevin,
> >>
> >> I highly recommending the entire ITK Software Guide:
> >>    http://www.itk.org/ItkSoftwareGuide.pdf
> >>
> >> For your specific question, see section 8.8.
> >>
> >> In short:
> >>
> >> IdentityTransform: identity
> >> TranslationTransform: n-D translation
> >> ScaleTransform: n-D scaling
> >> CenteredRigid2DTransform: 2-D rotation + translation
> >> Similarity2DTransform: 2-D scaling + rotation + translation
> >> VersorTransform: 3-D rotation
> >> VersorRigid3DTransform: 3-D rotation + translation
> >> Similarity3DTransform: 3-D scaling + rotation + translation
> >> AffineTransform: n-D scaling + rotation + translation + shear
> >>
> >> HTH
> >>
> >> Cheers, Dan
> >>
> >> On 21 November 2010 13:49, Kevin Neff <kevin.l.neff at gmail.com> wrote:
> >> >
> >> > I need to register images using rotation and translation.  Is that
> >> > possible
> >> > with theITK classes, or do I have to write my own?
> >> >
> >> > I'm basing this question on a translation-only example and the list of
> >> > classes derived from AffineTransform
> >> >
> >> > http://www.itk.org/Wiki/ITK_Image_Registration
> >
> >
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