Hanif G Khalak
hkhalak at osf1.gmu.edu
Fri Oct 17 14:38:30 EST 1997
Francois Vandermeersch (fvanderm at info.fundp.ac.be) wrote:
: I am trying to create some software which visualizes the fusion
: of two images. My software
: receives matched medical images and it visualizes the superposition of
: these images. On the
: screen, you can change the percentage of superposition of the images :
I think that 'superposition' has a different meaning than 'fusion'.
John Strout's suggestions about Photoshop's layering approach may be
a way to get a 'superposition' of the two images.
Fusion, as it is used in the image processing community, usually implies
'co-registration' of some sort. That is taking one image (or average
of images) as the template, transforming the other(s) contrast/intensities
into the same morphology (that of the template). This is often used
in fusing MRI/CAT (structural) images with PET/fMRT (functional) images
in 2/3-D medical applications.
: Ex. : taking two matched images A and B, in normal case, the
: result of the superposition
: shows on the screen, 50 % of the image A, 50 % of the image B. You can
: change the % of
: superposition. You can visualize for example that the fusionned image
: is composed of 60% of A and 40% of B
: or 80 % of B and 20 % of A, ... This software must conserve the
: contrast, color of the source
I am not sure what you mean by X% of image A. Is that X% of some measure
of the morphology/shape, or the rms intensity, or ?? Or all of the above?
The weighted average of two images (a single 'smoothed' compromise image)
is a bit different, I think, than what you want (or is it?). But in any
case, how do you 'conserve' contrast/color - in the X% sense?
With 'co-registration', you have to decide what the template is going to be
(one image), and what you get as a result are N images that represent
transformed versions of the original images you wanted to co-register.
This is often useful when you have images of N patients, and you
want to do comparative analysis across patients, on collocated data.
Please understand - I am not criticizing your question. I'm interested
in what you mean, and the answer. :-)
: I don't know of any techniques to do that. If you have some
: information about these techniques,
: some litterature (or reference), some algorithms, please E-mail me.
Try Morphology Digest :
There is also a web page for SPM, a medical image registration and stat
analysis package in MATLAB, but I couldn't find it at this moment.
Hanif Khalak, hkhalak at gmu.edu
Institute for Computational Sciences & Informatics,
George Mason University, Fairfax, VA 22030, USA
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