vol_hessian_blobness — 3D `feature` op

• Data kinds: voxel → voxel

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

Usage

Blob-like (spherical) response from the Hessian eigenvalues at one *scale*.

A bright blob has all three eigenvalues negative and comparable in magnitude;

the response is the geometric mean of their magnitudes,

`(|l1| |l2| |l3|)**(1/3)`, gated to voxels where the three share the sign of

a blob of the requested polarity (all negative for bright, all positive for

dark). Normalised to `[0, 1]`. Complements the line filters — a Frangi-style

`Rb` term rejects blobs, this one keeps them. Reference: the second-order

(Hessian) blob measure, cf. Frangi et al. 1998 / Lindeberg scale-space blobs.

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).*

vol_hessian_blobness — 3D feature op