Thickness calculation on binary 3D images
Compute the thickness of a solid using Anthony J. Yezzi’s method described in the article “An Eulerian PDE Approach for Computing Tissue Thickness, IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 22, NO. 10, OCTOBER 2003”: http://dx.doi.org/10.1109/tmi.2003.817775
A C implementation by Rubén Cárdenes can be found at http://www.dtic.upf.edu/~rcardenes/Ruben_Cardenes/Software.html and helped me write this, especially the anisotropic part.
numpy, cython, scikit-image. Tested with Debian Jessie and Fedora 24, miniconda-python 3.5.2, cython 0.24, numpy 1.11.2, scikit image 0.12.3
Available on pypi: https://pypi.python.org/pypi/pyezzi . Use pip: pip install pyezzi
Alternatively, clone the repository and build cython modules with python setup.py build_ext --inplace.
from pyezzi.thickness import compute_thickness thickness = compute_thickness(labeled_image, debug=True)
labeled_image is a 3 dimensional numpy array where the wall is labeled 2 and the interior is labeled 1.
A spacing parameter specifying the spacing between voxels along the axes can optionnaly be specified.
Check out the included jupyter notebooks in the example folder for more details.
Feel free to submit pull requests. I know the code is nowhere near optimal as it is.
You’re free to use and modify the code, but please cite me and the original paper.