TubeTK/Events/2010.10.19

• Dashboard: https://www.kitware.com/CDash/index.php?project=TubeTK
  • Registration re-write needed
• Wiki Documentation: http://public.kitware.com/Wiki/TubeTK

Stephen

Completed

• Ridge extractor success
• Email requests for TubeTK
• Licensing changes
• Blur3D -> Blur

Ongoing

• Radius extractor tests
  • 2D and 3D only :(
• Funding re-allocation

Upcoming

• Application in plant biology
• Proposal with Paul / Liz

Romain

• Implementation on the ComputeTortuosity module (only Distance Metric)
  • Started debugging

• Future
  • More debugging! ---> hopefully testing soon
  • #tube command
  • Implementation of the other 2 methods : ICM SOAM

Danielle

Sliding organ registration

• Fixed "duh" problem from Thursday - extracting tangential and normal components before computing regularization
• Regularization smoothing in normal direction completed
• Added intensity distance function (mean squares)

XCAT phantom

• Got XCAT running on my machine (thanks Andinet!)
• Learned XCAT parameters
• Wrote isbiValidation.py:
  • --basic (XCAT mode 0 - phantom mode): with respiratory period 5s and cardiac period 1s, generates two images at 0s and 2.5 s, saves as .mhd
  • --gold (XCAT mode 2 - spherical lesion generation mode): creates gold standard motion field, and saves as .txt (index, vector in 6 columns). Then run itkImageToImageDiffusiveDeformableRegistrationGenerateGoldStandardTest to create itk::Image<VectorType, Dimension> .mhd for visualization
    • XCAT phantom gives gold standard vectors for surface borders (XCAT mode 4), but no internal vectors! So...
    • for index in range - generate spherical lesion at index, use nurbs_save = 1 to save lesion.nrb, then calculate centroid of lesion control points

• • --segmentation (XCAT mode 5 - save anatomical variation mode, or run XCAT mode 0 with save_nurbs = 1) to save surfaces (.nrb text file). Then create new .txt file for the surface you want. Then run itkImageToImageDiffusiveDeformableRegistrationGenerateNormalsTest to create itk::Image<PixelType, Dimension> of control points
    • Unfortunately: (1) control points need interpolation, can't find NURBS support in VTK; (2) XCAT has MANY types of surfaces for one organ - ex all intracardiac surfaces, etc, and it would be a lot of work to sort through them; (3) Perfect segmentation not great for registration method evaluation - removes segmentation error component of total error.
    • Ex: right lung

Talking points

• Underlying XCAT deformation fields too perfect? They are likely interpolating the border vectors.

Future

• Boundary conditions
• Compute weighting term = distance to organ border
• Extract organ border normals from input data
• Run registration + compare to gold standard for validation #s