vol_rle_intersect — 3D `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"))

Usage

Intersection of two RLE regions on the runs (no decode).

> The detailed description below is the original text — the summary and the headings are translated.

`vol_rle_union と同じ掃引エンジン(_rle_boolean`)で、区間ごとの被覆状態が

`ia & ib`(両方の内側)の区間だけを run として残す。計算量は run 数に対して

O(n log n) で、voxel 数には依存しない。

返り値: 同じ `shape の新しい VolRLE`。共通部分が無ければ run 0 本の region

(エラーではない。空かどうかは `len(region) == 0 か vol_rle_volume` で見る)。

`vol_rle_decode(result) == decode(a) & decode(b)` が voxel 単位で成り立つ。

検証(`ValueError): どちらかが VolRLE` でない・run 配列の整合性検査に失敗 /

`a.shape != b.shape`。

使いどころ: ROI(`vol_rle_encode した domain マスク)と成分(vol_rle_components`)

の重なり判定、2 つの閾値結果の共通領域、`vol_rle_volume` と組み合わせた

IoU 計算(`|a∩b| / |a∪b|`)を密配列なしで行う。

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)

• rle_region_efficiency — py -3.11 examples_3d/rle_region_efficiency.py

Ops the type connects to (they accept `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

Same category (`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).*

vol_rle_intersect — 3D rle_region op