[Insight-users] Registering US -> CT

[Luis Ibanez]

Hi Neilson,

MutualInformation is mostly a region-based image metric.
This means that its value gets better when the overlap
between matching regions of the image is large. Mutual
Information is not particularly well suited for matching
thin structures since thir random sampling is unlikely
to select many pixels belonging to those structures.

In that sense you probably shouldn't expect much from Mutual
Information for registering Bone, since bone structures are
mostly shell-like and they don't fill large regions of space.
E.g. large bones have their layers of cortical bone with high
calcifications but their width usually cover just a couple of
pixels in a CT scan.

Given that you seem to have segmented the bone from the CT scan,
it is probably worth to try a Model-to-Image registration approach.
This can be done by taking points on the surface of your bone
segmentation, and/or from a band around that surface, and using
them to match the intensities (and structure) of the same bone as
seen in the UltraSound images.

Could you post a couple of the US images ?

(e.g. you could put them in www.mypacs.net and let us know their
  image ID).


Depending on how the bone structures look like on the US image
there may be different possible metrics to try in a PointSet to
Image registration.


BTW, when you start working in 3D, don't attempt to use Rigid
transforms until you have manage to tune all the other parameters
of the registration to work with simple translation transforms.
It is more effective to deal with a single issue at a time.



Regards,


     Luis



-------------------------------
N.E. Mackenzie Mackay wrote:

> Hi,
> 
>     I have tried for the last while to get a single ultrasound image to 
> register to a CT volume.  Specifically try to get the bone of an 
> ultrasound image and bone of the CT to register together.  Up to now I 
> am having quite some trouble.
> 
> I have been able to segment the bone from CT and give an estimate on 
> where the bone is in the ultrasound.  I am now trying to register those 
> two images.
> 
> This is what I am using:
> 
> MattesMutualInformationImageToImageMetric - decided to use this because 
> the registration was of two different modalities.  Couldn't use feature 
> registration becuase to hard to segment ultrasound correctly
>     - using 50 bins and %20-%100 of samples still doesn't give adequate 
> results.
> 
> linearInterpolateImageFunction
> 
> RegularSetGradientDecentOptimizer
> 
> Euler3DTransform
> 
> Both images ( 3D CT and US ) are normalized before the registration.
> 
> I have used a maximum step ranging from 0.5-6.  And a min step of 0.005 
> - 1.
> 
> I have a good initial guess ( maximum 2cm away from correct with about 
> 0- 30degrees of rotation)> 
> I tested out the registration method in 2D and have had success.  When I 
> use the exact same variables applied in 3D the registration is poor.
> 
> Does anyone have any suggestions?  I would be happy to provide a couple 
> of images or actual code to show you what I am dealing with.
> 
> Neilson
> 
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