Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Tutorial on using ellipsoid actor to visualize tensor ellipsoids for DTI #818

Merged
merged 11 commits into from
Aug 8, 2023

Conversation

tvcastillod
Copy link
Contributor

This PR consists of a tutorial that is intended to show two ways of displaying diffusion tensor ellipsoids for DTI visualization. The first is using the basic tensor_slicer actor which allows us to slice many tensors as ellipsoids, and the second with the generic ellipsoid actor I'm currently working on (#791), which can be used to display different amounts of ellipsoids. The idea is to show the use that can be made of the ellipsoid actor in the visualization of diffusion tensor ellipsoids, compared to the tensor_slicer actor, contrasting visual quality and the amount of data that can be rendered.

I still working on this, it is not ready for review yet.

@ganimtron-10
Copy link
Contributor

Hey @tvcastillod,
I tried out the tutorials and they are fabulous, the visualization looks beautiful.

@codecov
Copy link

codecov bot commented Jul 24, 2023

Codecov Report

Merging #818 (8e97473) into master (2bba1b9) will decrease coverage by 0.04%.
Report is 57 commits behind head on master.
The diff coverage is n/a.

Impacted file tree graph

@@            Coverage Diff             @@
##           master     #818      +/-   ##
==========================================
- Coverage   84.33%   84.30%   -0.04%     
==========================================
  Files          44       44              
  Lines       10356    10353       -3     
  Branches     1410     1406       -4     
==========================================
- Hits         8734     8728       -6     
- Misses       1252     1255       +3     
  Partials      370      370              

see 3 files with indirect coverage changes

@tvcastillod tvcastillod changed the title [WIP] Tutorial on using ellipsoid actor to visualize tensor ellipsoids for DTI Tutorial on using ellipsoid actor to visualize tensor ellipsoids for DTI Jul 24, 2023
Copy link
Contributor

@skoudoro skoudoro left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Nice Tutorial @tvcastillod.

docs/examples/viz_dt_ellipsoids.py Outdated Show resolved Hide resolved
docs/examples/viz_dt_ellipsoids.py Show resolved Hide resolved
docs/examples/viz_dt_ellipsoids.py Show resolved Hide resolved
Copy link
Contributor

@skoudoro skoudoro left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Excellent Tutorial ! Thank you @tvcastillod, this is great and explain well the difference.

I am going ahead and merge this PR. Thank you

Comment on lines +58 to +73

class Sphere:
def __init__(self, vertices, faces):
self.vertices = vertices
self.faces = faces


sphere100 = Sphere(vertices, faces)

###############################################################################
# Now we are ready to create the ``tensor_slicer`` actor with the values of a
# brain slice. We also define the scale so that the tensors are not so large
# and overlap each other.

tensor_slice = actor.tensor_slicer(evals=slice_evals, evecs=slice_evecs,
sphere=sphere100, scale=.3)
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Can you create an issue with this part of the tutorial. We should remove the need of a sphere object.

@skoudoro skoudoro merged commit 2aecb57 into fury-gl:master Aug 8, 2023
23 of 30 checks passed
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

4 participants