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aimio-py

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Python bindings for the Numerics88 AimIO C++ library.

aimio-py provides a small Python API to read and write AIM files as NumPy arrays, read ISQ, SCV, and GOBJ files, inspect metadata, and work with processing logs.

Features

  • Read AIM files into NumPy arrays
  • Write AIM files from NumPy arrays
  • Read ISQ files into NumPy arrays
  • Read SCV scout-view files into NumPy arrays
  • Read GOBJ contour masks into binary NumPy volumes
  • Read AIM, ISQ, SCV, or GOBJ files with single read_image and image_info dispatchers
  • Access AIM, ISQ, SCV, and GOBJ header metadata (aim_info, isq_info, scv_info, gobj_info)
  • Convert processing logs between text and dictionary formats
  • Optional density/HU conversion helpers

Installation

From PyPI (recommended):

pip install aimio-py

From source:

git clone https://github.com/wallematthias/aimio-py.git
cd aimio-py
git submodule update --init --recursive
pip install -e .

Quickstart

from py_aimio import image_info, read_image, write_aim

array, meta = read_image("scan.AIM")
print(meta["origin"], meta["spacing"], meta["direction"])

header = image_info("scan.AIM")
write_aim("copy.AIM", array, meta)

The matching metadata CLI uses the same format resolution:

aimio-info scan.AIM
aimio-info mask.GOBJ --format gobj

Reading Options

read_image() detects AIM, ISQ, SCV, and GOBJ files from the extension and forwards any extra keyword arguments to the format-specific reader.

aim, aim_meta = read_image("scan.AIM", density=True)
isq, isq_meta = read_image("scan.ISQ", unit="density")
scout, scout_meta = read_image("scout.SCV")
mask, mask_meta = read_image("mask.GOBJ", value=1, crop="tight")

The format-specific readers are also available directly:

  • AIM: read_aim(path, density=False, hu=False)
  • ISQ: read_isq(path, unit="native"), where unit can be "native", "hu", "density", or "bmd"
  • SCV: read_scv(path)
  • GOBJ: read_gobj(path, value=127, crop="tight"), where crop can be "tight" or "header"

At the moment, AIM and ISQ default to native stored values. For calibrated bone workflows, request density/BMD explicitly with density=True for AIM or unit="density"/unit="bmd" for ISQ.

API

  • read_image(path, format="auto", **kwargs) -> (array, meta)
  • image_info(path, format="auto") -> meta

Format-specific readers and metadata helpers are also available:

  • read_aim(path, density=False, hu=False) -> (array, meta)
  • read_isq(path, unit="native") -> (array, meta)
  • read_scv(path) -> (array, meta)
  • read_gobj(path, value=127, crop="tight") -> (array, meta)
  • aim_info(path), isq_info(path), scv_info(path), gobj_info(path)
  • write_aim(path, array, meta=None, unit=None)
  • get_aim_density_equation(processing_log)
  • get_aim_hu_equation(processing_log)
  • log_to_dict(log)
  • dict_to_log(dct)

Read metadata includes SimpleITK-style geometry keys for both AIM and ISQ: origin, spacing, and direction. For AIM, spacing is copied from element_size and origin follows the ITKIOScanco-compatible convention: (position + offset) * spacing. The older vtkbone-style half-voxel-shifted origin is also exposed as vtkbone_origin. For ISQ, spacing comes from the ISQ header and origin defaults to (0.0, 0.0, 0.0). direction currently defaults to the 3D identity direction, matching the practical behavior observed from ITKIOScanco for ISQ files without explicit orientation metadata.

GOBJ files are read as contour masks. Additive contours are rasterized as filled contours including their boundary. Subtractive contours, such as inner cortical boundaries, remove only the strict contour interior so the contour boundary remains part of the mask. crop="tight" returns the contour bounding box, while crop="header" returns the full CTDATA header grid.

Development

Run tests:

pytest -q

Run tests with coverage:

pytest -q --cov=py_aimio --cov-report=term-missing --cov-report=xml:coverage.xml

Build local artifacts:

python -m build --wheel --sdist

Build documentation from docstrings:

pip install sphinx
make -C docs html

Generated HTML will be in docs/build/html/index.html.

Important build note

This project depends on the external/AimIO and external/n88util git submodules. If they are missing, extension builds will fail.

Attribution

  • py_aimio/calibration.py is adapted from Bonelab/Bonelab.
  • py_aimio/header_log.py is by Matthias Walle.
  • py_aimio/scv.py and py_aimio/gobj.py are by Matthias Walle and Andrew Burghardt.

License

MIT

Metadata

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This release

0.1.9 This release

21 release files

0.1.8

17 release files

0.1.7

17 release files

0.1.1

17 release files

0.1.0

18 release files

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