vol_distance_transform — 3D `medial` op

• Data kinds: voxel → voxel

• Call: import fullseye as fs; fs.ledger.vol_distance_transform(vol_binary, spacing=None) (to call the implementation directly, import volops; volops.vol_distance_transform(vol_binary, spacing=None); from the registry, ops3d.get("vol_distance_transform"))

Usage

Exact Euclidean distance transform of a binary volume.

Each foreground (non-zero) voxel is labelled with its Euclidean distance to

the nearest background voxel, via `scipy.ndimage.distance_transform_edt`.

Pass *spacing* `(sz, sy, sx) (e.g. VolumeMeta.spacing_mm`, or the

`VolumeMeta` itself) to make the distance anisotropy-aware — millimetres

rather than voxels; otherwise unit spacing is assumed. A non-`{0, 1}` input

is thresholded at `> 0.5`.

Returns a `(D, H, W)` float64 distance field (0 on the background).

Reference: Felzenszwalb & Huttenlocher, Theory of Computing 2012.

References (sample data, literature)

• 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.

Runnable examples (verified samples that actually call this op)

• medial_topology — py -3.11 examples_3d/medial_topology.py

• molecule_atom_count — py -3.11 examples_3d/molecule_atom_count.py

• vessel_metrology — py -3.11 examples_3d/vessel_metrology.py

Ops the type connects to (they accept `voxel` as input)

voxel_to_mips · voxel_to_mesh · signed_distance_field · to_points · sobel3d · hessian3d · curvature_maps · edt_jfa

Same category (`medial`)

distance_ridge · skeletonize_vol · medial_axis_points · topology_signature · medial_match · skeleton_junctions3d · skeleton_endpoints3d · skeleton_prune3d

*Provenance: volops.py — 3D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

vol_distance_transform — 3D medial op