Hi
Some ideas for 1-3:
Segment by threshold the different grey regions (not only the edges),
calculate from each region the distance transform ("Process -> Binary -
> Distance Map") the skeleton ("Process -> Binary -> Skeletonize").
The distance times 2 plus 1 at each location of the skeleton, is a not
to bad estimate of the thickness in unities of pixels.
Karsten
Am 22.01.2009 um 10:15 schrieb Thomas Theelen:
> Dear all,
>
> I want to do the following:
> 1. Segment OCT images by automatically detecting different gray
> value areas (I think this works best with edge detection?)
> 2. Mark these borders with lines, following the border contour
> 3. Measure the distance between lines to get tissue thickness
> curves
> 4. Apply the thickness curves to several images in a stack to get
> thickness maps or 3D reconstructions of layers
> This seems very complex. I would be happy for advice for at least
> points
> 1-3.
> Linked is a typical image. Analysis should take place in 8-bit.
>
> Link to foto:
>
http://picasaweb.google.nl/lh/photo/ouTkCBXor7pY-YOGYsDR2Q?authkey=5XvSk> ES-bF4&feat=directlink
>
> Many thanks, Thomas
>
> ____________________________________________
>
> Thomas Theelen, M.D.
> Radboud University Nijmegen Medical Centre
> Department of Ophthalmology (409)
> Philips van Leydenlaan 15
> 6525 EX Nijmegen, The Netherlands
> Phone: +31-24-361 44 48
> Fax: +31-24-354 05 22
>
>
>
>
>
>
> Het UMC St Radboud staat geregistreerd bij de Kamer van Koophandel
> in het handelsregister onder nummer 41055629.
> The Radboud University Nijmegen Medical Centre is listed in the
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> 41055629.
Karsten
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