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Install

The desktop app is the recommended dicomqc interface. The CLI supports automation and scripted workflows; both use the same Python audit engine.

Desktop App​

Desktop availability

Installers have not been published. To run the app now, follow the desktop source-build instructions. You need Python, Node.js, Rust, and the operating system's Tauri prerequisites.

Once it is running, try the Desktop privacy audit example.

CLI​

Install from PyPI with Python 3.10 or newer. The PyPI package installs the CLI, not the desktop app.

Install from PyPI​

Create an isolated environment so dicomqc and its dependencies do not alter the system Python installation:

python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install dicomqc

Verify the installed command and version:

dicomqc --version

Upgrade an existing installation with:

python -m pip install --upgrade dicomqc

Optional MultiQC installation​

dicomqc writes standalone HTML reports without extra packages. Install MultiQC only if you want to combine dicomqc results with other QC reports:

python -m pip install multiqc

See the scan walkthrough for the rendering command and its matching report screenshots.

Install from source​

From a repository checkout, install dicomqc and its runtime dependencies in editable mode:

python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install -e .

Contributors who need pytest and coverage tooling can install the test optional dependency group:

python -m pip install -e ".[test]"

The test extra is not needed for normal use.

For the complete suite, including the optional local API, install ".[test,api,api-test]". The desktop app has separate native build requirements; installing the PyPI package provides the CLI.

External DICOM tools​

DCMTK, Orthanc, and other pseudonymization or remediation tools are not dicomqc dependencies. Install them separately only when they are part of the local DICOM transformation workflow. dicomqc itself remains read-only.

Continue with the Desktop example or CLI walkthrough to run your first audit with synthetic data.