[Insight-developers] Mattes mutual information metric additions

[Miller, James V (GE, Research)]

Karthik,

I would have thought MI would have gracefully handled the situation of 
regions with very high intensities. The MI value does not use the intensity
value itself in the metric computation, just the probability that that
intensity maps to another intensity in the other image.  If these regions
of high intensity do not map consistenly to another intensity in the other
image, then they should appear as baseline noise to the metric and have
little effect.

What could be having an affect is how the pdfs are constructed. When
you have a few pixels of high intensity, the sampling of the pdf (bin widths)
gets out of whack and you loose resolution in the pdf for the features
(intensities) you are really interested in. Since the pdf representation becomes 
inaccurate, I could see the registration failing if this happens.

This is classic problem in kernel density estimation.  There are several 
strategies to address it: non-uniform bins, hierarchical pdfs, band-width
selection techniques, etc.  Perhaps one of these solutions should be 
investigated.

The approach that you are proposing essentially censors the data.  I am not 
sure that I am in favor of this at the Mattes metric layer.  Perhaps
data censorship could be handled at a higher level whereby all image 
metrics could benefit.  Data censorship usually leads to a set a 
robust statistical techniques (M-estimators to replace least squares, etc.).
These would have general applicability and solve a number of problems
in image registration (registering data pre- and post-implant, etc.).

Alternatively, you could transform the PET data to SUV (standard uptake value)
instead of using the raw counts.  This would bring the dynamic range 
of the data down to [0, 6] or so.  There are many formulas for calculating
SUV based on data in the DICOM header.

Jim





-----Original Message-----
From: insight-developers-bounces+millerjv=crd.ge.com at itk.org
[mailto:insight-developers-bounces+millerjv=crd.ge.com at itk.org]On Behalf
Of Karthik Krishnan
Sent: Tuesday, May 30, 2006 2:04 PM
To: Lydia Ng
Cc: Insight-developers (E-mail)
Subject: [Insight-developers] Mattes mutual information metric additions


Hi,

We've had PET-CT datasets, (the PET ones in particular) with intensity 
distributions where certain regions have very high pixel intensities 
that tend to throw the registration off course. I added some code to the 
mattes that optionally allows the joint PDF computation of the metric to 
be restricted to a fixed range of intensities and it seems to work well.

The API is simple. There are 4 optional methods : 
SetFixedImageLowerBound( ), SetMovingImageLowerBound( ), 
SetFixedImageUpperBound( ), SetMovingImageUpperBound( ).

I've attached the patch and I would like to commit it, but I want to 
confirm with the author or others in case you think its just code 
clutter and I should tailor a derived class for my needs.

Thanks
-karthik

PS: Just to clarify, setting the bounds is different from using a 
rescale intensity
filter on the fixed and moving images prior to computing the metric.
Rescale intensity filters clamp the intensities at the bounds. Therefore,
you will have an intensity peak at the bounds that also contributes to
estimation of the joint intensity PDF's and distorts the histogram.