xsitk_confidence_connected — 2D `extra` op

• Data kinds: image → region

• Call: fullseye.apply(img, "xsitk_confidence_connected", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

> This operator's description has not been translated yet. The original text follows as it is.

信頼区間連結領域拡張(SimpleITK `ConfidenceConnected`)。画像中心を種にし、現在の領域内の平均・標準偏差から「平均 ± multiplier * 標準偏差」の区間を作り、それを反復的に更新しながら連結領域を広げていく(xsitk_connected_threshold より統計的な閾値の決め方)。

`a は反復回数(1+int(a*5) で 1〜6)、b は標準偏差の倍率(1.0+3.0*b` で 1〜4)を振る。初期近傍半径は 2 固定。画像中心付近に対象があることを前提とした op。

Detailed usage guide

• gallery2d_color_artistic family guide

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.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• gallery2d_color_artistic — py -3.11 examples/gallery2d_color_artistic.py

Ops the type connects to (they accept `region` as input)

identity · reg_erode · reg_dilate · reg_open · reg_close · fill_holes · select_largest · remove_small

Same category (`extra`)

xsitk_curvature_flow · xsitk_minmax_curv_flow · xsitk_curv_aniso_diff · xsitk_laplacian_sharpen · xsitk_grayscale_fillhole · xsitk_grayscale_grindpeak · xsitk_opening_by_recon · xsitk_closing_by_recon

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

xsitk_confidence_connected — 2D extra op