edt_jfa — 3D feature op

• Data kinds: voxel → sdf

• Call: import match3d; match3d.edt_jfa(seed_bool, device='cpu') (or ops3d.get("edt_jfa"))

• GPU: this op has a GPU path (device="cuda")

Usage

3-D Euclidean distance transform via the Jump Flooding Algorithm (GPU). Each voxel → the distance to its nearest seed.

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)

• diff_features — py -3.11 examples_3d/diff_features.py

Ops the type connects to (they accept sdf as input)

sdf_to_occupancy · fuse_to_voxel · integrate · extract_surface_points · query_distance · sdf_union · sdf_intersect · sdf_subtract

Same category (feature)

sobel3d · hessian3d · curvature_maps · vol_frangi · vol_sato · vol_hessian_blobness · vol_gradient_magnitude · vol_local_maxima

*Provenance: match3d.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.