[Insight-users] Using MI-metrics with image couples that have huge size differences

[Floca, Ralf]

I have used itk in different registration task so far and it worked
fine. Working on my current task I came across a problem using mutual
information metrics (e.g. Mattes MI). I have two images: Image 1
(modality: CT angiography; 160x160x112 mm) and Image 2 (modality:
rotation angiography; size 47x47x47 mm).

If I define Image 1 as the fixed image (which would be more suitable
regarding other parts of the application), the registration normally
fails in the first step, because to many samples are mapped outside the
moving image. Looking at the sizes of the image, it becomes clear that
the chances for that behavior are pretty high. Image 2 (even if the
transform is initialized with total coverage) covers only around 4% of
Image 1, therefore with randomly drawn samples it is pretty probable
that less than 25% samples will be drawn successfully. So the metric
exception will be thrown.

A workaround would be to switch both images; but I would appreciate
another way, if possible. Modifying the metric in a generic way, to be
aware of the moving image limitations, seems not possible, because on
the level of itk::Transform there is no possibility to map fixed image
samples onto moving image samples.

If anybody can give me a hint which metric would be suitable for my task
or how I can manage the problem with the MI metrics in a sound way, I
would be very thankful.

Best regards,
Ralf o Floca

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Ralf Floca
University of Heidelberg                           
Institute for Medical Biometry and Informatics
Department of Medical Informatics
Im Neuenheimer Feld 400            
D-69120 Heidelberg, Germany                Tel. : +49 (0)6221 56-7484  
http://www.klinikum.uni-heidelberg.de/mi   Fax  :               -4997

ralf.floca at med.uni-heidelberg.de           Sekr.:               -7483
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