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        "author": "Aditya Panchal",
        "author_email": "apanchal@bastula.org",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "Intended Audience :: Healthcare Industry",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Natural Language :: English",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering :: Medical Science Apps.",
            "Topic :: Scientific/Engineering :: Physics"
        ],
        "description": "dicompyler-core\n===============\n\n|Binder| |pypi| |travis-ci| |coveralls| |Codacy| |Codecov| |Documentation Status| |Zenodo|\n\nA library of core radiation therapy modules for DICOM / DICOM RT used by `dicompyler <http://www.dicompyler.com>`__. This\npackage includes:\n\n-  ``dicomparser``: parse DICOM objects in an easy-to-use manner\n-  ``dvh``: Pythonic access to dose volume histogram (DVH) data\n-  ``dvhcalc``: Independent DVH calculation using DICOM RT Dose & RT Structure Set\n\nOther information\n-----------------\n\n-  Free software: `BSD license <https://github.com/dicompyler/dicompyler-core/blob/master/LICENSE>`__\n-  Documentation: `Read the docs <https://dicompyler-core.readthedocs.io>`__\n-  Tested on Python 2.7, 3.5, 3.6\n\nDependencies\n------------\n\n-  `numpy <http://www.numpy.org>`__ 1.2 or higher\n-  `pydicom <https://pydicom.github.io>`__ 0.9.9 or higher (pydicom 1.0 compatible)\n-  `matplotlib <http://matplotlib.org>`__ 1.3.0 or higher (for DVH calculation)\n-  `six <https://pythonhosted.org/six/>`__ 1.5 or higher\n-  Optional:\n\n   -  `Pillow <https://pillow.readthedocs.io>`__ (for image display)\n   -  `Shapely <https://github.com/Toblerity/Shapely>`__ (for structure volume calculation)\n   -  `scikit-image <http://scikit-image.org/>`__ (for DVH interpolation)\n\nBasic Usage\n------------\n\n.. code-block:: python\n\n    from dicompylercore import dicomparser, dvh, dvhcalc\n    dp = dicomparser.DicomParser(\"rtss.dcm\")\n\n    # i.e. Get a dict of structure information\n    structures = dp.GetStructures()\n\n    >>> structures[5]\n    {'color': array([255, 128, 0]), 'type': 'ORGAN', 'id': 5, 'empty': False, 'name': 'Heart'}\n\n    # Access DVH data\n    rtdose = dicomparser.DicomParser(\"rtdose.dcm\")\n    heartdvh = dvh.DVH.from_dicom_dvh(rtdose.ds, 5)\n\n    >>> heartdvh.describe()\n    Structure: Heart\n    DVH Type:  cumulative, abs dose: Gy, abs volume: cm3\n    Volume:    437.46 cm3\n    Max Dose:  3.10 Gy\n    Min Dose:  0.02 Gy\n    Mean Dose: 0.64 Gy\n    D100:      0.00 Gy\n    D98:       0.03 Gy\n    D95:       0.03 Gy\n    D2cc:      2.93 Gy\n\n    # Calculate a DVH from DICOM RT data\n    calcdvh = dvhcalc.get_dvh(\"rtss.dcm\", \"rtdose.dcm\", 5)\n\n    >>> calcdvh.max, calcdvh.min, calcdvh.D2cc\n    (3.0899999999999999, 0.029999999999999999, dvh.DVHValue(2.96, 'Gy'))\n\nAdvanced Usage and Examples can be found in Binder: |Binder|\n\nCiting dicompyler-core\n----------------------\nA DOI for dicompyler-core with various citation styles can be found at Zenodo: |Zenodo|\n\n\nCredits\n-------\n\nThis package was created with\n`Cookiecutter <https://github.com/audreyr/cookiecutter>`__ and the\n`audreyr/cookiecutter-pypackage <https://github.com/audreyr/cookiecutter-pypackage>`__ project template.\n\n.. |Binder| image:: http://mybinder.org/badge.svg\n   :target: http://mybinder.org/repo/bastula/dicom-notebooks\n.. |pypi| image:: https://img.shields.io/pypi/v/dicompyler-core.svg\n   :target: https://pypi.python.org/pypi/dicompyler-core\n.. |travis-ci| image:: https://img.shields.io/travis/dicompyler/dicompyler-core.svg\n   :target: https://travis-ci.org/dicompyler/dicompyler-core\n.. |coveralls| image:: https://coveralls.io/repos/github/dicompyler/dicompyler-core/badge.svg?branch=master\n   :target: https://coveralls.io/github/dicompyler/dicompyler-core?branch=master\n.. |Codacy| image:: https://api.codacy.com/project/badge/Grade/39060fc468844402a4030715fe01bb15\n   :target: https://www.codacy.com/app/bastula/dicompyler-core?utm_campaign=Badge_Coverage\n.. |Codecov| image:: https://codecov.io/gh/dicompyler/dicompyler-core/branch/master/graph/badge.svg\n   :target: https://codecov.io/gh/dicompyler/dicompyler-core\n.. |Documentation Status| image:: https://readthedocs.org/projects/dicompyler-core/badge/?version=latest\n   :target: https://dicompyler-core.readthedocs.io/en/latest/\n.. |Zenodo| image:: https://zenodo.org/badge/51550203.svg\n   :target: https://zenodo.org/badge/latestdoi/51550203\n\n\n",
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