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Update (Solution) -17 October 2020-

I finally did it! You can check the code on my GitLab repo. The function is to do this is the domain_extract which identifies the meshed boundaries to separate. To check a working example, you can check the sphere_meshing.py file, under the Scripts/Meshing directory.

Issue description

I am working on human brain tACS simulations where I have the models of the skin, skull, csf, brain and ventricles in STL format. The shape does not matter and there are no intersections. I want to run FE analysis and use SfePy but the only problem I have so far is how to define the volume regions. Using pymesh I am able to generate a pretty detailed and good mesh using the following code:

import pymesh

skin_stl = pymesh.load_mesh('skin.stl')
skull_stl = pymesh.load_mesh('skull.stl')
csf_stl = pymesh.load_mesh('csf.stl')
brain_stl = pymesh.load_mesh('brain.stl')

model = pymesh.merge_meshes( (skin_stl, skull_stl, csf_stl, brain_stl) )
model_tet = pymesh.tetrahedralize(model, 10)

The meshing I get from the code above can be seen in the following picture. enter image description here

As you can see the boundaries are clear and the meshing algorithm took that into consideration. If I get the number of components of this mesh it is 4 as it should be since I have 4 bounding surfaces. Using the following code I am able to separate and get the vertices and faces of the above tessellated mesh.

new_mesh = pymesh.form_mesh(model_tet.vertices, model_tet.faces)
sep_mesh = pymesh.separate_mesh(new_mesh)

I can not in any way separate the mesh and get the voxels included in between two consecutive bounding surfaces. Is there a way to do that using pymesh or something else?

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