Cython bindings to the CAT-Surface library (libCAT) for cortical surface analysis
Project description
cat-surf — Python bindings for CAT-Surface
cat-surf provides Python access to CAT-Surface,
a mature C/C++ toolkit for surface-based neuroimaging analysis, focusing on the processing and analysis of cortical surface meshes.
CAT-Surface has been used internally for more than 10 years as part of CAT12, the SPM toolbox for computational anatomy. With this package, it is now distributed as an independent Python package for direct integration into external workflows to make CAT-Surface easier to use:
- in T1Prep workflows (currently relying on CAT-Surface binaries)
- in Python-based pipelines without subprocess-heavy wrappers
- in reproducible environments via published wheels
Installation
pip install cat-surf
Pre-built wheels are available for:
- macOS — arm64 (Apple Silicon), x86_64 (Intel)
- Linux — x86_64, aarch64 (manylinux)
- Python 3.9 – 3.13
Basic usage
import cat_surf
# Check version
print(cat_surf.__version__)
# Load a surface file (GIFTI, FreeSurfer, BIC/MNI formats)
vertices, faces = cat_surf.read_surface("lh.central.gii")
# Per-vertex area
area, total_area = cat_surf.get_area(vertices, faces)
# Euler characteristic
chi = cat_surf.euler_characteristic(vertices, faces)
# Smooth per-vertex data (heat kernel, FWHM in mm)
smoothed = cat_surf.smooth_heatkernel(vertices, faces, area, fwhm=20.0)
Surface operations
| Function | Description |
|---|---|
read_surface / write_surface |
Multi-format surface I/O (GIFTI, FreeSurfer, BIC) |
read_values / write_values |
Per-vertex scalar I/O |
get_area |
Per-vertex and total surface area |
get_area_normalized |
Area normalized by a reference sphere |
euler_characteristic |
Topological integrity check |
smooth_heatkernel |
Heat-kernel smoothing of per-vertex data |
smooth_mesh |
Laplacian/Taubin mesh vertex smoothing |
smoothed_curvatures |
Mean curvature estimation |
sulcus_depth |
Sulcal depth via depth potential |
reduce_mesh |
Quadric mesh decimation |
remove_intersections |
Self-intersection repair |
count_intersections |
Count self-intersecting faces |
surf_average |
Vertex-wise averaging across surfaces |
surf_to_sphere |
Inflate surface to sphere |
sphere_radius |
Mean radius of a spherical surface |
correct_thickness_folding |
Folding-based thickness correction |
point_distance |
Vertex-to-surface point distances (symmetric) |
point_distance_mean |
Mean vertex-to-surface distance |
hausdorff_distance |
Hausdorff distance between two surfaces |
Volume operations
| Function | Description |
|---|---|
vol_sanlm |
Structure-adaptive non-local means denoising |
vol_blood_vessel_correction |
Blood vessel intensity correction |
vol_thickness_pbt |
Cortical thickness via projection-based method |
vol_amap |
Adaptive maximum a posteriori tissue segmentation |
vol_marching_cubes |
Isosurface extraction from a volume file |
Conversion utilities
| Function | Description |
|---|---|
arrays_to_polygons |
Convert NumPy vertex/face arrays to internal polygon mesh |
polygons_to_arrays |
Convert internal polygon mesh back to NumPy arrays |
Typical use cases
- Cortical mesh processing (resampling, smoothing, metrics)
- Thickness and folding related computations
- Volume-to-surface projection
- Denoising and volume preprocessing for structural MRI
Citation / provenance
If you use this package in research, please cite Dahnke et al., 2013 and mention the cat-surf package version for reproducibility.
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