Metadata-Version: 1.1
Name: WORC
Version: 2.1.2
Summary: Workflow for Optimal Radiomics Classification.
Home-page: https://github.com/MStarmans91/WORC
Author: M. Starmans
Author-email: m.starmans@erasmusmc.nl
License: Apache License, Version 2.0
Description: |Build Status|
        
        WORC v2.1.2
        ===========
        
        Workflow for Optimal Radiomics Classification
        ---------------------------------------------
        
        WORC is an open-source python package for the easy execution of full
        Radiomics pipelines.
        
        We aim to establish a general Radiomics platform supporting easy
        integration of other tools. With our modular build and support of
        different software languages (python, MATLAB, ruby, java etc.), we want
        to facilitate and stimulate collaboration, standardisation and
        comparison of different Radiomics approaches. By combining this in a
        single framework, we hope to find a universal Radiomics strategy that
        can address various problems.
        
        Disclaimer
        ----------
        
        This package is still under development. We try to thoroughly test and
        evaluate every new build and function, but bugs can off course still
        occur. Please contact us through the channels below if you find any and
        we will try to fix them as soon as possible, or create an issue on this
        Github.
        
        Tutorial
        --------
        
        The WORC tutorial is hosted in a `separate
        repository <https://github.com/MStarmans91/WORCTutorial>`__.
        
        Documentation
        -------------
        
        For more information, see our the Wiki on this Github.
        
        Alternatively, you can generate the documentation by checking out the
        master branch and running from the root directory:
        
        ::
        
            python setup.py build_sphinx
        
        The documentation can then be viewed in a browser by opening
        ``PACKAGE_ROOT\build\sphinx\html\index.html``.
        
        Installation
        ------------
        
        WORC currently only supports Unix with Python 2 (>2.7.6) systems.
        Windows is not supported, although WORC can still work under windows.
        
        Please first install PREDICT:
        
        ::
        
              pip install PREDICT
        
        The package can be installed through pip:
        
        ::
        
              pip install WORC
        
        Alternatively, you can directly install WORC from this repository:
        
        ::
        
              python setup.py install
        
        Make sure you install the requirements first:
        
        ::
        
              pip install -r requirements.txt
        
        Several tools have some (mandatory) prerequisites which are listed
        below. We highly recommend you to install these to maximally profit from
        our toolbox.
        
        PREDICT
        ~~~~~~~
        
        Most of the default tools in WORC use
        `PREDICT <https://github.com/Svdvoort/PREDICTFastr>`__, our in-house
        feature extraction and classification toolbox. Currently, you do need to
        manually install PREDICT from the Github or with pip:
        
        ::
        
              pip install PREDICT
        
        Fastr Configuration
        ~~~~~~~~~~~~~~~~~~~
        
        The installation will create a FASTR configuration file in the
        $HOME/.fastr/config.d folder. This file is used for configuring fastr,
        the pipeline execution toolbox we use. More information can be found at
        `the FASTR
        website <http://fastr.readthedocs.io/en/stable/static/file_description.html#config-file>`__.
        In this file, so called mounts are defined, which are used to locate the
        WORC tools and your inputs and outputs. Please inspect the mounts and
        change them if neccesary.
        
        Only if you are using FASTR < 1.3.0, you need to manually add the WORC
        tools, datatypes and mounts to your FASTR configuration
        ($HOME/.fastr/config.py). This concerns the following additions:
        
        Optional: Graphviz
        ~~~~~~~~~~~~~~~~~~
        
        WORC can draw the network and save it as a SVG image using
        `graphviz <https://www.graphviz.org/>`__. In order to do so, please make
        sure you install graphviz:
        
        ::
        
              apt install graphiv
        
        Optional: Elastix
        ~~~~~~~~~~~~~~~~~
        
        Image registration is included in WORC through `elastix and
        transformix <http://elastix.isi.uu.nl/>`__. In order to use elastix,
        please download the binaries and place them in your
        fastr.config.mounts['apps'] path. Check the elastix tool description for
        the correct subdirectory structure. For example, on Linux, the binaries
        and libraries should be in "../apps/elastix/4.8/install/" and
        "../apps/elastix/4.8/install/lib" respectively.
        
        Note: optionally, you can tell WORC to copy the metadata from the image
        file to the segmentation file before applying the deformation field.
        This requires ITK and ITKTools: see the `Install\_ITK
        file <Install_ITK.md>`__ for installation instructions. More info on
        using the copying of metadata can be found on our Github Wiki.
        
        Optional: XNAT
        ~~~~~~~~~~~~~~
        
        We use the XNATpy package to connect the toolbox to the XNAT online
        database platforms. You will only need this when you want to download or
        upload data from or to XNAT. We advise you to specify your account
        settings in a .netrc file when using this feature, such that you do not
        need to input them on every request:
        
        ::
        
            echo "machine images.xnat.org
            >     login admin
            >     password admin" > ~/.netrc
            chmod 600 ~/.netrc
        
        3rd-party packages used in WORC:
        --------------------------------
        
        -  FASTR (Workflow design and building)
        -  xnat (Collecting data from XNAT)
        -  SimpleITK (Image loading and preprocessing)
        -  `Pyradiomics <https://github.com/Radiomics/pyradiomics>`__
        -  Our in-house package
           `PREDICT <https://github.com/Svdvoort/PREDICTFastr>`__
        
        See for other requirements the `requirements file <requirements.txt>`__.
        
        Start
        -----
        
        We suggest you start with the `WORC
        Tutorial <https://github.com/MStarmans91/WORCTutorial>`__. Besides a
        Jupter notebook with instructions, we provide there also an example
        script for you to get started with. Make sure you input your own data as
        the sources. Also, check out the unit tests of several tools in the
        WORC/resources/fastr\_tests directory. The example is explained in more
        detail in the Wiki on this Github.
        
        WIP
        ---
        
        -  We are working on improving the documentation.
        -  We are working on organizing clinically relevant datasets for
           examples and unit tests.
        -  We will merge to Python 3 support in the coming months (April 2019),
           as soon as FASTR moves to Python 3.
        
        License
        -------
        
        This package is covered by the open source `APACHE 2.0
        License <APACHE-LICENSE-2.0>`__.
        
        When using WORC, please cite this repository.
        
        Contact
        -------
        
        We are happy to help you with any questions. Please contact us on the
        `WORC google
        group <https://groups.google.com/forum/#!forum/worc-users>`__.
        
        We welcome contributions to WORC. We will soon make some guidelines. For
        the moment, converting your toolbox into a FASTR tool will be
        satisfactory.
        
        .. |Build Status| image:: https://travis-ci.com/MStarmans91/WORC.svg?token=qyvaeq7Cpwu7hJGB98Gp&branch=master
           :target: https://travis-ci.com/MStarmans91/WORC
        
Keywords: bioinformatics radiomics features
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Healthcare Industry
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Education
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: System :: Distributed Computing
Classifier: Topic :: System :: Logging
Classifier: Topic :: Utilities
