[Insight-users] MattesMutualInformation metric: Fixed and moving image desired features

[Karthik Krishnan]

On Tue, Nov 3, 2009 at 7:12 AM, Oscar Esteban Sanz-Dranguet <
oesteban at die.upm.es> wrote:

> Hi,
>
> I'm trying to perform intra-subject rigid registration between MR & SPECT
> images. I would like the MR to be the fixed image, BUT I've found that if I
> use the SPECT as fixed, the registration is more quick and accurate. Why
> does it happen?
>

It should be quicker, using a lower resolution image as the fixed image, for
most metrics. The metric is evaluated at each sample point on the fixed
image, typically all voxels in the fixed image.

Most metrics sample the whole fixed image. With Mattes, contrary to what you
report, one would expect the times to be roughly the same (assuming that you
have the same number of samples in both cases).

The final resampling step though, should be a lot faster using the fixed
image as the low res image, since the moving image is resampled to the fixed
image grid, ie the iterator walks through every pixel in the fixed image and
computes the intensity of the moving voxel that resamples onto this
location.



>
> The images are as follows:
>
> - SPECT: 128x128x43,
>              3,32237mmx3,32237mmx3,32237
>              less than 255 levels of gray
>
> - MR: 224x240x256
>         0,85mmx0,9mmx0,85mm
>         512 levels of gray
>
>
> Image preprocessing:
> - I use a IntensityWindowingImageFilter to rescale the intensities to the
> range 0,255.
> - I use a DiscreteGaussianImageFilter with deviation 2.0 to the two images,
> but I've tried using a lot of different values and combinations. It appears
> to be the same
> - I use ScalarImageToHistogramGenerator to find the first maximum of the
> two images histogram. With it, I use the metric's  member
> SetFixedImageSamplesIntensityThreshold for the fixed image and I remove the
> background of the moving image with ThresholdImagefilter. The values used
> for the two thresholds is the value of the first maximum + 10% of overall
> frequencies.
> - Resampling SPECT to MR's spacing and size improves the registration, when
> using MR as fixed and adequate values of optimizer scales (they are in a
> very tiny range)
>
> Initialization:
> - Using Moments, the SPECT image starts a little lower (10mm) on the Z axis
>
> Metric:
> - 70 bins, 10000 samples
>
> Optimizer:
> - SPSA or Gradient Descent. I use a visualization pipeline with VTK to test
> that the scales and the step size make sense.
>
>
> Thanks in advance. Cheers.
>
> --
> Oscar Esteban
> BIT - UPM (http://www.die.upm.es/im/)
> +34 913 366 827 ext.4248
>
> _____________________________________
> Powered by www.kitware.com
>
> Visit other Kitware open-source projects at
> http://www.kitware.com/opensource/opensource.html
>
> Kitware offers ITK Training Courses, for more information visit:
> http://www.kitware.com/products/protraining.html
>
> Please keep messages on-topic and check the ITK FAQ at:
> http://www.itk.org/Wiki/ITK_FAQ
>
> Follow this link to subscribe/unsubscribe:
> http://www.itk.org/mailman/listinfo/insight-users
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://www.itk.org/pipermail/insight-users/attachments/20091103/f4cb54b3/attachment-0001.htm>