pacsanini 0.2.1

A package for DICOM utilities.

pacsanini

pacsanini 🎻 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.

Documentation

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.

Contributing and Code of Conduct

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.

Installation

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

For development

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

Usage with docker

A docker image can be built locally to run pacsanini within an isolated environment.

docker image build -t pacsanini:latest .
docker run pacsanini --help

Roadmap

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.