pacsanini
๐ป is a package designed to help with the collection of DICOM files and the extraction
of DICOM tags (metadata) for structuring purposes.
pacsanini
's functionalities come out of a desire to facilitate research in
medical imagery by easing the process of data collection and structuring.
The two main pain points for this are:
- acquiring data from a PACS
- extracting metadata from DICOM files in research-ready formats (eg: csv)
The project seeks to target medical/research professionals that are not necessarily familiar with coding but wish to obtain data sets and software engineers that wish to build applications with a certain level of abstraction.
Check out the complete documentation on readthedocs.
You will be able to find examples on how to use the pacsanini
API from within you Python application
and as a command line tool.
All contributions to improve pacsanini
are welcome and valued. For more information on how you can contribute,
please read the Contributing document and make sure that you are familiar with our
Code of Conduct.
You are also more than welcome to open a discussion on our GitHub discussions page.
To install a particular release version, check out the available versions of pacsanini
on PyPI
or simply run the following command to obtain the latest release:
pip install pacsanini
To obtain the cutting edge version of pacsanini
, you can use pip
or poetry
in the following way:
pip install git+https://github.com/Therapixel/pacsanini.git
# or
poetry add git+https://github.com/Therapixel/pacsanini.git
poetry
is the only supported build tool for installing pacsanini
in a development context.
See the previous section on how to install poetry
.
git clone https://github.com/Therapixel/pacsanini.git
cd pacsanini
poetry install --no-root --no-dev
# or, to install the project and its development dependencies:
poetry install --no-root
A docker image can be built locally to run pacsanini
within an isolated environment.
docker image build -t pacsanini:latest .
docker run pacsanini --help
The following topics are the main areas where pacsanini
can improve as a library and a tool.
Of course, these topics are up for discussion and such discussions are encouraged in the
GitHub issues section.