[Insight-users] compute an abs. and rel. distance-field image based on a start front, an obstacle image and a finish front

[Dr. Roman Grothausmann]

Dear mailing list members,


Starting with two binary images, I want to compute a distance-field image  in a 
way that the first binary image is regarded as the start front and the second 
binary image represents obstacles in the way of the propagation front. From what 
I've read about similar problems either fast-marching or geodesic filters can 
supply the output I'm looking for.
What itk-filter do I need for that? The itkReconstructionByDilationImageFilter 
seems only to take one input image although in the description a marker and a 
mask image are mentioned. The itkFastMarchingImageFilter seems to need a speed 
image, can that be constant, i.e. can it be the binary image containing the 
obstacles or would I have to supply a distance-map of the obstacle image?

In a second step I'd like to normalize the absolute distance field image of the 
previous result. For that I want to supply a third binary image. The 
normalization should be done in a way that the abs. distance field image is 
adjusted such that it contains relative distance, i.e. between 0 and 1. The 
values of the abs. distance field should be adjusted such that the pixels of the 
shortest paths from any of the pixels making up the propagation start front to 
the finish front (contained in the third binary image) should linearly increase 
from 0 to 1. I'm not sure if this can be done because possibly the solution is 
not well/uniquely defined.
Any ideas or comments on this are very welcome.

Thanks for any help or hints
Roman



-- 
Dr. Roman Grothausmann

Tomographie und Digitale Bildverarbeitung
Tomography and Digital Image Analysis

Institut für Funktionelle und Angewandte Anatomie, OE 4120
Medizinische Hochschule Hannover
Carl-Neuberg-Str. 1
D-30625 Hannover

Tel. +49 511 532-9574