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dicomtrolley\n\n[![CI](https://github.com/sjoerdk/dicomtrolley/actions/workflows/build.yml/badge.svg?branch=main)](https://github.com/sjoerdk/dicomtrolley/actions/workflows/build.yml?query=branch%3Amain)\n[![PyPI](https://img.shields.io/pypi/v/dicomtrolley)](https://pypi.org/project/dicomtrolley/)\n[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/dicomtrolley)](https://pypi.org/project/dicomtrolley/)\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n[![Checked with mypy](http://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org/)\n\nRetrieve medical images via WADO-URI, WADO-RS, QIDO-RS, MINT, RAD69 and DICOM-QR\n\n* Uses `pydicom` and `pynetdicom`. Images and query results are `pydicom.Dataset` instances\n* Query and download DICOM Studies, Series and Instances\n* Integrated search and download - automatic queries for missing series and instance info\n\n![A trolley](docs/resources/trolley.png)\n\n[dicomtrolley docs on readthedocs.io](https://dicomtrolley.readthedocs.io)\n\n## Installation\n```\npip install dicomtrolley\n```\n\n## Basic usage\n```python\n# Create a http session\nsession = requests.Session()\n\n# Use this session to create a trolley using MINT and WADO\ntrolley = Trolley(searcher=Mint(session, \"https://server/mint\"),\n                  downloader=WadoURI(session, \"https://server/wado_uri\"))\n\n# find some studies (using MINT)\nstudies = trolley.find_studies(Query(PatientName='B*'))\n\n# download the fist one (using WADO)\ntrolley.download(studies[0], output_dir='/tmp/trolley')\n```\n\n## Documentation\nSee [dicomtrolley docs on readthedocs.io](https://dicomtrolley.readthedocs.io)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsjoerdk%2Fdicomtrolley","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsjoerdk%2Fdicomtrolley","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsjoerdk%2Fdicomtrolley/lists"}