medial op• Data kinds: voxel × voxel → measurement
• Call: import fullseye as fs; fs.ledger.medial_match(vol_a, vol_b, w_topology=0.6, w_radius=0.4, n_bins=12) (to call the implementation directly, import medial; medial.medial_match(vol_a, vol_b, w_topology=0.6, w_radius=0.4, n_bins=12); from the registry, ops3d.get("medial_match"))
A coarse matching score between two voxel shapes based on their medial (topology + radius distribution). Returns [0,1].
Combines, with weights, the distance between the skeletons' topology descriptors (fractions of endpoint/branch/normal/isolated) and the distance between the medial radius distributions (histograms of inscribed radii), and returns similarity = 1 - distance. The closer to 1, the more similar. Roughly invariant to translation and rotation (90 degrees); used for topology-based initial matching (coarse screening).
Args:
vol_a, vol_b: binary voxels (bool / 0-1 3D).
w_topology: weight of the topology distance (default 0.6).
w_radius: weight of the radius-distribution distance (default 0.4).
n_bins: number of bins of the radius histogram.
Returns:
float: similarity score [0,1] (larger is more similar).
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• medial_topology — py -3.11 examples_3d/medial_topology.py
measurement as input)vol_gaussian_psf · fuse_to_voxel · fresnel_reflectance · snell_angle
medial)distance_ridge · skeletonize_vol · medial_axis_points · topology_signature · skeleton_junctions3d · skeleton_endpoints3d · skeleton_prune3d · skeleton_branches3d
*Provenance: medial.py — 3D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.