Domains From Segmented 3D Images

[GoogleCodeExporter]

I would like to create a 3d Mesh from a segmented medical image (I want to 
recreate all the point 3.3 of 
http://doc.cgal.org/latest/Mesh_3/index.html#Chapter_3D_Mesh_Generation)

But i dont know if cgal-bindings has the methods to do it, like Image_3 and 
poisson reconstruction, if the answer its negative, theres  a way to construct 
those method with the existing ones, other way to do it, or even a way to 
include those methods manually?

This is for an investigation an it would be a big help i you can help me with 
this.

THANKS!

Original issue reported on code.google.com by [email protected] on 15 Jan 2014 at 11:23

[GoogleCodeExporter]

Is your input a .inr.gz file?
I haven't ported yet the  CGAL::Labeled_image_mesh_domain_3 class but it can be 
done quickly.
Poisson reconstruction has not yet been wrapped either.

Original comment by [email protected] on 16 Jan 2014 at 6:35

• Added labels: Type-Enhancement
• Removed labels: Type-Defect

[GoogleCodeExporter]

My image its not a .inr.gz but it could be converted easily. Whats the best 
solution ? its dificult to add the methods needed to do that?, the algorithm 
its very important for the analysis of medical images. The Poisson algorithm 
its also very important to do a 3d Mesh from point clouds.
If you could do something it would be awesome.

Thank you in advance for your support.

Original comment by [email protected] on 16 Jan 2014 at 8:34

[GabrielBalabanResearch]

Dear Sloriot, I have a medical image that I would like to mesh with CGAL via your python interface. Would it be possible for you to port CGAL::Labeled_image_mesh_domain_3? There are a few people in my lab that would love to do the same thing. Cheers Gabriel

[lrineau]

I want to add that the Python bindings should probably be updated to the new API of labeled mesh domain, since CGAL-4.13.

[reox]

I also stumbled over this: I want to replicate the gray level image surface mesh example in python, however it is hard to load images with CGAL directly - except you already have them in inr format. But it is very easy to use other libraries like (Simple)ITK or somehow convert the 3D image data into a numpy array and store voxel spacing, origin, ... separately. Most of the time (at least for me) I already have the image loaded elsewhere and just want to do some additional tasks with CGAL. Therefore, some function to convert an array to an Image_3 class would be super useful!