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dvha-mlca-0.2.3.post1

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0.2.3.post1
0.2.3
0.2.2
0.2
0.1rc1
0.2.3.post1
0.2.3
0.2.2
0.2
0.1rc1

توضیحات

Batch analyze DICOM-RT Plan files to calculate Complexity Scores
ویژگی مقدار
سیستم عامل -
نام فایل dvha-mlca-0.2.3.post1
نام dvha-mlca
نسخه کتابخانه 0.2.3.post1
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Dan Cutright
ایمیل نویسنده dan.cutright@gmail.com
آدرس صفحه اصلی https://github.com/cutright/DVHA-MLCA
آدرس اینترنتی https://pypi.org/project/dvha-mlca/
مجوز MIT License
DVHA MLC Analyzer ================= |logo| |build| |Docs| |pypi| |python-version| |lgtm| |lgtm-cq| |Codecov| |lines| |repo-size| |code-style| Batch analyze DICOM-RT Plan files to calculate complexity scores `DVH Analytics <https://github.com/cutright/DVH-Analytics>`__ (DVHA) is a software application for building a local database of radiation oncology treatment planning data. It imports data from DICOM-RT files (i.e., plan, dose, and structure), creates a SQL database, provides customizable plots, and provides tools for generating linear, multi-variable, and machine learning regressions. DVHA-MLCA is a stand-alone command-line script to batch analyze DICOM-RT Plans using the MLC Analyzer code from DVHA. Complexity score based on: Younge KC, Matuszak MM, Moran JM, McShan DL, Fraass BA, Roberts DA. Penalization of aperture complexity in inversely planned volumetric modulated arc therapy. Med Phys. 2012;39(11):7160–70. Installation ------------ To install via pip: .. code-block:: console $ pip install dvha-mlca If you've installed via pip or setup.py, launch from your terminal with: .. code-block:: console $ mlca <init-scanning-directory> If you've cloned the project, but did not run the setup.py installer, launch DVHA-MLCA with: .. code-block:: console $ python mlca/main.py <init-scanning-directory> Command line usage ------------------ .. code-block:: console usage: mlca [-h] [-of OUTPUT_FILE] [-xw COMPLEXITY_WEIGHT_X] [-yw COMPLEXITY_WEIGHT_Y] [-xs MAX_FIELD_SIZE_X] [-ys MAX_FIELD_SIZE_Y] [-ver] [-v] [-n PROCESSES] [init_dir] Command line DVHA MLC Analyzer positional arguments: init_dir Directory containing DICOM-RT Plan files optional arguments: -h, --help show this help message and exit -of OUTPUT_FILE, --output-file OUTPUT_FILE Output will be saved as dvha_mlca_<version>_results_<time-stamp>.csv by default. -xw COMPLEXITY_WEIGHT_X, --x-weight COMPLEXITY_WEIGHT_X Complexity coefficient for x-dimension: default = 1.0 -yw COMPLEXITY_WEIGHT_Y, --y-weight COMPLEXITY_WEIGHT_Y Complexity coefficient for y-dimension: default = 1.0 -xs MAX_FIELD_SIZE_X, --x-max-field-size MAX_FIELD_SIZE_X Maximum field size in the x-dimension: default = 400.0 (mm) -ys MAX_FIELD_SIZE_Y, --y-max-field-size MAX_FIELD_SIZE_Y Maximum field size in the y-dimension: default = 400.0 (mm) -ver, --version Print the DVHA-MLCA version -v, --verbose Print final results and plan summaries as they are analyzed -n PROCESSES, --processes PROCESSES Enable multiprocessing, set number of parallel processes For example: .. code-block:: console $ mlca "C:\PatientDicom" -n 8 Directory: C:\PatientDicom Begin file tree scan ... File tree scan complete Searching for DICOM-RT Plan files ... 100%|██████████████████████████████| 9087/9087 [00:59<00:00, 153.52it/s] 1650 DICOM-RT Plan file(s) found Analyzing 1650 file(s) ... 10%|███ | 169/1650 [02:02<13:35, 1.82it/s] Dependencies ------------ * `Python <https://www.python.org>`__ >3.5 * `Pydicom <https://github.com/darcymason/pydicom>`__ * `NumPy <http://numpy.org>`__ * `Shapely <https://github.com/Toblerity/Shapely>`__ * `tqdm <https://github.com/tqdm/tqdm>`__ Support ------- If you like DVHA-MLCA and would like to support our mission, all we ask is that you cite us if we helped your publication, or help the DVHA community by submitting bugs, issues, feature requests, or solutions on the `issues page <https://github.com/cutright/DVHA-MLCA/issues>`__. Cite ---- DOI: `https://doi.org/10.1002/acm2.12401 <https://doi.org/10.1002/acm2.12401>`__ Cutright D, Gopalakrishnan M, Roy A, Panchal A, and Mittal BB. "DVH Analytics: A DVH database for clinicians and researchers." Journal of Applied Clinical Medical Physics 19.5 (2018): 413-427. .. |build| image:: https://github.com/cutright/DVHA-MLCA/workflows/build/badge.svg :target: https://github.com/cutright/DVHA-MLCA/actions :alt: build .. |pypi| image:: https://img.shields.io/pypi/v/dvha-mlca.svg :target: https://pypi.org/project/dvha-mlca :alt: PyPI .. |python-version| image:: https://img.shields.io/pypi/pyversions/dvha-mlca.svg :target: https://pypi.org/project/dvha-mlca :alt: PyPI .. |lgtm-cq| image:: https://img.shields.io/lgtm/grade/python/g/cutright/DVHA-MLCA.svg?logo=lgtm&label=code%20quality :target: https://lgtm.com/projects/g/cutright/DVHA-MLCA/context:python :alt: lgtm code quality .. |lgtm| image:: https://img.shields.io/lgtm/alerts/g/cutright/DVHA-MLCA.svg?logo=lgtm :target: https://lgtm.com/projects/g/cutright/DVHA-MLCA/alerts :alt: lgtm .. |Codecov| image:: https://codecov.io/gh/cutright/DVHA-MLCA/branch/master/graph/badge.svg :target: https://codecov.io/gh/cutright/DVHA-MLCA :alt: Codecov .. |Docs| image:: https://readthedocs.org/projects/dvha-mlca/badge/?version=latest :target: https://dvha-mlca.readthedocs.io/ :alt: Documentation Status .. |code-style| image:: https://img.shields.io/badge/code%20style-black-000000.svg :target: https://github.com/psf/black :alt: Code style: black .. |lines| image:: https://img.shields.io/tokei/lines/github/cutright/dvha-mlca :target: https://img.shields.io/tokei/lines/github/cutright/dvha-mlca :alt: Lines of code .. |repo-size| image:: https://img.shields.io/github/languages/code-size/cutright/dvha-mlca :target: https://img.shields.io/github/languages/code-size/cutright/dvha-mlca :alt: Repo Size .. |logo| image:: https://user-images.githubusercontent.com/4778878/92505112-351c7780-f1c9-11ea-9b5c-0de1ad2d131d.png :width: 400 :alt: DVHA logo


نیازمندی

مقدار نام
- numpy
- pydicom
- shapely[vectorized]
- tqdm


زبان مورد نیاز

مقدار نام
>3.5 Python


نحوه نصب


نصب پکیج whl dvha-mlca-0.2.3.post1:

    pip install dvha-mlca-0.2.3.post1.whl


نصب پکیج tar.gz dvha-mlca-0.2.3.post1:

    pip install dvha-mlca-0.2.3.post1.tar.gz