Hi Ged,
> It sounds like you want to do something a little like the spatially
> adaptive filtering in Davatzikos' paper:
> http://dx.doi.org/10.1006/nimg.2000.0655
> so it might be worth asking if he has code available.
That may be an option; however, the paper seems to use an atlas-based
adaptive smoothing which I do not want: I want to exclude certain
regions within an image based on characteristics calculated before.
> I'm not sure I follow you here... did you write a new conv2 function
> that did something special when the kernel included NaNs? If so, what
> did you do, and in what way were the results too widespread?
I am far too inept to write something like this, but I can google and
find a Matlab NaN-toolbox atw
ww.koders.com/matlab/fid70E036E1A9D4D670CB0059D87E628207AB026EA0.aspx
However, the problem was exactly as you described, with this working in
2D but not in 3D.
> Does that sound reasonable?
It sounds interesting, but I will have to work on it to find out if it's
imeplementable by me ;)
> I don't know if this kind of thing has been
> investigated much in the signal processing literature... I think
> usually, when people move away from standard smoothing, they start
> looking at more complicated anisotropic diffusion models, which I'm
> afraid I don't know too much about... (some of the refs in the
> Davatzikos paper above should help here)
I have also thought about looking into bilateral spatial filtering as
done before (Neuroimage. 2006 Nov 1;33(2):564-9) but am not done yet
(will I ever be? ;)
> Best of luck, and happy Christmas/days!
The same to you! And I will play around with your PS-solution and let
you knwo!
Thanks,
Marko
--
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Marko Wilke (Dr.med./M.D.)
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Universitäts-Kinderklinik University Children's Hospital
Abt. III (Neuropädiatrie) Dept. III (Pediatric neurology)
Hoppe-Seyler-Str. 1, D - 72076 Tübingen
Tel.: (+49) 07071 29-83416 Fax: (+49) 07071 29-5473
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