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WORC-3.6.0
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مشاهده بیشترتوضیحات
Workflow for Optimal Radiomics Classification.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | OS Independent |
| نام فایل | WORC-3.6.0 |
| نام | WORC |
| نسخه کتابخانه | 3.6.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Martijn P. A. Starmans |
| ایمیل نویسنده | m.starmans@erasmusmc.nl |
| آدرس صفحه اصلی | https://github.com/MStarmans91/WORC |
| آدرس اینترنتی | https://pypi.org/project/WORC/ |
| مجوز | Apache License, Version 2.0 |
WORC v3.6.0
===========
Workflow for Optimal Radiomics Classification
---------------------------------------------
Information
-----------
+---------------------+---------------------+---------------------+---------------+
| Unit test | Documentation | PyPi | Citing WORC |
+=====================+=====================+=====================+===============+
| |image0| | |image1| | |image2| | |image3| |
+---------------------+---------------------+---------------------+---------------+
Introduction
============
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.
License
-------
This package is covered by the open source `APACHE 2.0
License <APACHE-LICENSE-2.0>`__.
When using WORC, please cite this repository as following:
``Martijn P.A. Starmans, Sebastian R. van der Voort, Thomas Phil and Stefan Klein. Workflow for Optimal Radiomics Classification (WORC). Zenodo (2018). Available from: https://github.com/MStarmans91/WORC. DOI: http://doi.org/10.5281/zenodo.3840534.``
For the DOI, visit |image4|.
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 and Documentation
--------------------------
The WORC tutorial is hosted in a `separate
repository <https://github.com/MStarmans91/WORCTutorial>`__.
The official documentation can be found at https://worc.readthedocs.io.
Installation
------------
WORC supports Unix and Windows systems with Python 3.6+: the `unit
tests <https://github.com/MStarmans91/WORC/actions?query=workflow%3A%22Unit+test%22>`__
are performed on the latest Ubuntu and Windows versions with Python 3.7.
For detailed installation instructions, please check `the ReadTheDocs
installation
guidelines <https://worc.readthedocs.io/en/latest/static/quick_start.html#installation>`__.
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
3rd-party packages used in WORC:
--------------------------------
- SimpleITK (Image loading and preprocessing)
- `Pyradiomics <https://github.com/radiomics/pyradiomics>`__
- `PREDICT <https://github.com/Svdvoort/PREDICTFastr>`__
- scikit-learn
- imbalanced-learn
- xgboost
- `fastr (Workflow design and
building) <http://fastr.readthedocs.io>`__
- `ComBat <https://github.com/Jfortin1/ComBatHarmonization>`__
(optional)
See for other python packages the `requirements
file <requirements.txt>`__.
Start
-----
We suggest you start with the `WORC
Tutorial <https://github.com/MStarmans91/WORCTutorial>`__. Besides a
Jupyter notebook with instructions, we provide there also an example
script for you to get started with.
WIP
---
- We are writing the paper on WORC.
- We are expanding the example experiments of WORC with open source
datasets.
Contact
-------
We are happy to help you with any questions. Please sent us a mail or
place an issue on the Github.
We welcome contributions to WORC. For the moment, converting your
toolbox into a FASTR tool is satisfactory: see also `the fastr tool
development
documentation <https://fastr.readthedocs.io/en/stable/static/user_manual.html#create-your-own-tool>`__.
Optional
--------
Besides the default installation, there are several optional packages
you could install to support WORC.
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. On Ubuntu, simply run
::
apt install graphiv
On Windows, follow the installation instructions provided on the
graphviz website. Make sure you add the executable to the PATH when
prompted.
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 ITKTools
github <https://github.com/ITKTools/ITKTools>`__ for installation
instructions.
XNAT
~~~~
We use the XNATpy package to connect the toolbox to the XNAT online
database platforms. You will only need this when you use the example
dataset we provided, or if 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 for your own datasets, such that you do not need
to input them on every request.
.. |image0| image:: https://github.com/MStarmans91/WORC/workflows/Unit%20test/badge.svg
:target: https://github.com/MStarmans91/WORC/actions?query=workflow%3A%22Unit+test%22
.. |image1| image:: https://readthedocs.org/projects/worc/badge/?version=latest
:target: https://worc.readthedocs.io/en/latest/?badge=latest
.. |image2| image:: https://badge.fury.io/py/WORC.svg
:target: https://badge.fury.io/py/WORC
.. |image3| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3840534.svg
:target: https://zenodo.org/badge/latestdoi/92295542
.. |image4| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3840534.svg
:target: https://zenodo.org/badge/latestdoi/92295542
نیازمندی
| مقدار | نام |
|---|---|
| >=3.5.0 | configparser |
| >=0.7.6 | drmaa |
| >=3.2.3 | fastr |
| >=0.6.1 | ghalton |
| ==0.7.0 | imbalanced-learn |
| <4.0,>=3.0.0 | jsonschema |
| >=0.21.1 | lifelines |
| >=5.0.1 | natsort |
| >=0.2.3 | neuroCombat |
| >=0.5.0 | nose-parameterized |
| >=1.3.7 | nose |
| >=1.16.3 | numpy |
| >=0.24.2 | pandas |
| >=3.1.15 | PREDICT |
| >=16.2.0 | pyOpenSSL |
| >=1.2.2 | pydicom |
| <=2.8.0 | python-dateutil |
| >=5.3.1 | pyyaml |
| ==0.23.1 | scikit-learn |
| <=1.5.4,>=1.2.1 | scipy |
| <=2.0.2,>=1.2.0 | SimpleITK |
| >=1.10.0 | six |
| >=1.4 | sphinx |
| >=3.5.1 | tables |
| >=0.9.3 | tikzplotlib |
| >=4.7.1 | tqdm |
| ==1.2.1 | xgboost |
| >=1.2.0 | xlrd |
| >=0.2.2 | xnat |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.6 | Python |
نحوه نصب
نصب پکیج whl WORC-3.6.0:
pip install WORC-3.6.0.whl
نصب پکیج tar.gz WORC-3.6.0:
pip install WORC-3.6.0.tar.gz