dactim-angio 0.1.1

À compléter : courte description du package

Dactim-angio

⚠️ À compléter : une phrase de description officielle du projet (objectif scientifique, contexte de l'équipe).

dactim_angio is a Python research library for angiographic image processing, providing spatial grids, projective geometry, radial basis function interpolation, and differentiable similarity metrics — building blocks for 2D/3D registration and reconstruction of vascular imaging.

Features

• Spatial grids (dactim_angio.spatial.grid)
  • Abstract SpatialGrid with push/pull coordinate transforms and finite-difference gradients
  • SpatialGridAffine — affine-mapped volumes, loadable directly from NIfTI files
  • SpatialGrid_XA — X-ray angiography grids built from NIfTI + JSON metadata (projection center, etc.)
  • Gaussian image pyramids, rescaling, scalar-field transfer between grids, and PyVista export
• Projective geometry (dactim_angio.spatial.geom)
  • PointCloud and RayFan primitives with KD-tree / BallTree spatial indexing
  • Sparse point–point, ray–ray and point–ray distance matrices (with analytic derivatives)
  • Camera model with field-of-view frustum and visibility queries
  • Parametrized affine transforms (rotation/translation) with closed-form derivatives
• Radial basis function interpolation (dactim_angio.spatial.RBF)
  • GaussianRBF over point clouds — evaluation on points or rays, with shape derivatives
  • GaussianRBF_rays over angular ray fans, plus L² / H¹₀ norm matrices
• Differentiable similarity metrics (dactim_angio.metrics)
  • Mutual information (kernel density estimator), Kraskov joint entropy, correlation, MSE
  • Each returns the metric value and its gradients, ready for gradient-based optimization

Installation

Requires Python ≥ 3.9.

From source:

git clone https://github.com/jdambrin/Dactim-angio.git
cd Dactim-angio
pip install .

Once published on PyPI:

pip install dactim-angio

Quick start

The snippet below is illustrative and follows the public API — adapt paths and field names to your data.

from dactim_angio.spatial.grid import SpatialGridAffine
from dactim_angio.metrics import mse

# Load a 3D volume from a NIfTI file
grid = SpatialGridAffine.fromNifti("patient.nii.gz")
print(grid)                      # shape + scalar-field summary

# Export to PyVista for 3D visualization
mesh = grid.toPyvista()

# Compute a differentiable similarity metric between two fields
value, grad_x, grad_y = mse(fixed_field, moving_field)

Package structure

dactim_angio/
├── metrics.py            # similarity metrics with analytic gradients
└── spatial/
    ├── geom.py           # point clouds, ray fans, cameras, affine transforms
    ├── grid.py           # spatial grids, NIfTI/DICOM I/O, pyramids
    └── RBF.py            # Gaussian RBF interpolation

Dependencies

numpy, scipy, matplotlib, nibabel, pydicom, pyvista, scikit-image, scikit-learn. These are installed automatically with the package.

License

This software is distributed under the CeCILL Free Software License Agreement v2.1 (see the LICENSE file). CeCILL is a copyleft license, GPL-compatible, governed by French law, authored by CEA, CNRS and Inria.

Citation

⚠️ Optionnel : si ce travail accompagne une publication, ajoute ici la référence à citer.