Hi! I’ve constructed a pipeline to segment and skeletonize axons in a 3D volume. However, I’m stuck with an analysis issue for extracting certain measurements from my images:

### Analysis goals

- I want to measure the local diameter along the axons to construct a cumulative probability distribution plot of axon diameters in my 3D volumes.
- My idea is as follows: in the rough schematic above, at a given point along the skeleton (blue), I would take the average length of a few rays (red) that cast outward from the skeleton. This would be the approximated diameter at that given point. Then I would repeat this for all the points along the skeleton in that image volume.

### Challenges

- I think the hardest part to wrap my head around is determining which direction the axon is traveling in order to determine the proper plane where the cross-section lies (i.e. differentiate between a cross-section vs. a surface).
- I am also open to measuring local cross-sectional area instead of local diameter, if that is too hard.
- Put simply, I don’t know where to start or what to do. Is there an algorithm in skimage or opencv that is similar to what I describe?
- I’ve read some examples about Rayburst sampling that seem to get at what I’m trying to do:
- Rayburst sampling, an algorithm for automated three-dimensional shape analysis from laser scanning microscopy images. https://www.nature.com/articles/nprot.2006.313
- Rapid Reconstruction of 3D Neuronal Morphology from Light Microscopy Images with Augmented Rayburst Sampling. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0084557

Please let me know if I can provide any further information. Any help is very much appreciated, thank you so much!