rle_region op• Data kinds: rle_region × rle_region → rle_region
• Call: import fullseye as fs; fs.ledger.vol_rle_intersect(a, b) (to call the implementation directly, import volregion; volregion.vol_rle_intersect(a, b); from the registry, ops3d.get("vol_rle_intersect"))
Intersection of two RLE regions on the runs (no decode).
With the same sweep engine as vol_rle_union (_rle_boolean), only the intervals whose per-interval coverage state is ia & ib (inside both) are kept as runs. The cost is O(n log n) in the number of runs and does not depend on the voxel count.
Returns: a new VolRLE with the same shape. If there is no common part, a region with 0 runs (not an error. Check emptiness with len(region) == 0 or vol_rle_volume). vol_rle_decode(result) == decode(a) & decode(b) holds voxel by voxel.
Validation (ValueError): either one is not a VolRLE or fails the run-array consistency check / a.shape != b.shape.
Where to use it: overlap tests between an ROI (a domain mask passed through vol_rle_encode) and components (vol_rle_components), the common region of 2 threshold results, and IoU computation combined with vol_rle_volume (|a∩b| / |a∪b|), all without a dense array.
• 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.
• rle_region_efficiency — py -3.11 examples_3d/rle_region_efficiency.py
rle_region as input)vol_rle_decode · vol_rle_volume · vol_rle_bbox · vol_rle_centroid · vol_rle_union · vol_rle_difference · fuse_to_voxel
rle_region)vol_rle_encode · vol_rle_decode · vol_rle_volume · vol_rle_bbox · vol_rle_centroid · vol_rle_union · vol_rle_difference · vol_rle_components
*Provenance: volregion.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.