phantomkit 0.1.2

Collection of tools to derive metrics from physical phantoms used in QA of medical imaging instruments.

PhantomKit

PhantomKit is a Python toolkit for automated quality assurance (QA) of medical imaging scanners using physical phantoms. It provides pydra-based workflows that register phantom scans to a reference template, extract per-vial signal statistics across multiple contrast types, and generate publication-quality plots — supporting both MRI and PET phantom protocols.

Features

• Template-based registration — iterative ANTs SyN registration with automatic orientation search across a rotation library
• Vial metric extraction — per-vial mean, median, std, min and max across all contrast images, written to CSV
• Plotting — scatter plots of vial intensity and parametric map plots (T1/IR, T2/TE) with mrview ROI overlays
• Protocol support — extensible protocols sub-package for phantom- and project-specific workflow configurations
• Parallel batch processing — pydra-native splitting and combining for multi-session datasets

Installation

python -m pip install phantomkit

Basic usage

from phantomkit.protocols.gsp_spirit import GspSpiritAnalysis

wf = GspSpiritAnalysis(
    input_image="/data/session01/t1_mprage.nii.gz",
    template_dir="/templates/gsp_spirit",
    output_base_dir="/results",
    rotation_library_file="/templates/gsp_spirit/rotations.txt",
)
outputs = wf(cache_root="/data/cache-root")

Or via the command line:

phantomkit run gsp-spirit /data/session01/t1_mprage.nii.gz \
    --template-dir /templates/gsp_spirit \
    --output-dir /results \
    --rotation-lib /templates/gsp_spirit/rotations.txt

License

Copyright 2026 Australian Imaging Service. Released under the Apache License 2.0.