vol_sato — 3D feature op

• Data kinds: voxel → voxel

• Call: import fullseye as fs; fs.ledger.vol_sato(vol, scales=(1, 2, 3), black_ridges=False) (to call the implementation directly, import volops; volops.vol_sato(vol, scales=(1, 2, 3), black_ridges=False); from the registry, ops3d.get("vol_sato"))

Usage

3-D Sato tubeness — the simpler two-eigenvalue line filter.

Per scale, from eigenvalues in algebraic order `e1 >= e2 >= e3` a bright

curvilinear (tube) structure has `e2, e3 < 0` and the tubeness is

`sqrt(e2 * e3) there (0 elsewhere); black_ridges=True` uses the two most

*positive* eigenvalues for dark tubes. The maximum over scales is normalised

to `[0, 1]`.

Cheaper and less selective than :func:vol_frangi (it does not explicitly

suppress plate- or blob-like structure), but a robust, well-cited tube

detector. Reference: Sato et al., Medical Image Analysis 1998.

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)

• 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 (feature)

sobel3d · hessian3d · curvature_maps · edt_jfa · vol_frangi · vol_local_std · vol_local_thickness · vol_orientation_coherence

*Provenance: volops.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.