{ "info": { "author": "Nicolas Cedilnik", "author_email": "nicoco@nicoco.fr", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Developers", "Intended Audience :: Education", "Intended Audience :: Science/Research", "Programming Language :: Python :: 3.6" ], "description": "======\npYezzi\n======\n\nCompute the thickness of a solid using Yezzi and Prince method described in\nthe article \"An Eulerian PDE Approach for Computing Tissue Thickness\", IEEE\nTRANSACTIONS ON MEDICAL IMAGING, VOL. 22, NO. 10, OCTOBER 2003. [#]_\n\nA C implementation by Rub\u00e9n C\u00e1rdenes [#]_ helped me a lot writing this,\nespecially the anisotropic part.\n\n.. [#] http://dx.doi.org/10.1109/tmi.2003.817775\n.. [#] http://www.dtic.upf.edu/~rcardenes/Ruben_Cardenes/Software.html\n\n\nRequirements\n============\n\nnumpy, cython, scikit-image. Tested with Debian Jessie and Fedora 27,\nminiconda-python 3.6, cython 0.24, numpy 1.11.2, scikit image 0.12.3\n\n\nInstallation instruction\n========================\n\nAvailable on pypi. [#]_\nUse pip: ``pip install pyezzi``\n\nAlternatively, clone the repository and build cython modules with\n``python setup.py build_ext --inplace``.\n\n.. [#] https://pypi.python.org/pypi/pyezzi\n\nUsage\n=====\n\n.. code:: python\n\n from pyezzi import compute_thickness\n thickness = compute_thickness(labeled_image, debug=True)\n\n``labeled_image`` is a 3 dimensional numpy array where the wall is labeled 2\nand the interior is labeled 1.\n\nA ``spacing`` parameter specifying the spacing between voxels along the axes\ncan optionnaly be specified.\n\nCheck out the included jupyter notebooks in the ``example`` folder for more\ndetails.\n\nNote on thickness solver implementation\n***************************************\n\nThe ordered traversal method mentioned in the original publication can be used\nusing the ``yezzi_solver='ordered'`` keyword argument. However, we found that\nit introduces artifacts to the result. Also the implementation is in pure\npython so it is slower to solve than the iterative algorithm.\n\nContributions\n=============\nFeel free to submit pull requests.\nI know the code is nowhere near optimal as it is.\n\nLicense\n=======\n\nThis work is licensed under the french CeCILL license. [#]_\nYou're free to use and modify the code, but please cite the original paper and\nme.\n\n.. 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