feature op• Data kinds: voxel → voxel
• Call: import fullseye as fs; fs.ledger.vol_gradient_magnitude(vol) (to call the implementation directly, import volops; volops.vol_gradient_magnitude(vol); from the registry, ops3d.get("vol_gradient_magnitude"))
3-D Sobel gradient magnitude `sqrt(gz**2 + gy**2 + gx**2)`.
> The detailed description below is the original text — the summary and the headings are translated.
Each `g* is a scipy.ndimage.sobel` derivative along one axis. The
response localises at intensity boundaries (a step edge lights up on the
interface and is ~0 in flat regions). Returns a `(D, H, W)` float64 volume.
計算: `scipy.ndimage.sobel` を axis 0 (z), 1 (y), 2 (x) の順に掛け、
`sqrt(gz**2 + gy**2 + gx**2)` を返す。Sobel は微分 [-1,0,1] と平滑 [1,2,1] の
分離カーネル(直交 2 軸で各 4 倍)なので、軸に垂直な単位ステップ(0→1)に対する
応答は 1 ではなく 16(界面をはさむ 2 voxel で 16.0、平坦部は 0。scipy の既定
重み・境界 `mode='reflect')。値は正規化しない([0, 1]` には収まらない)。
spacing は受けず、voxel 単位の差分(異方 voxel でも軸ごとに補正しない)。
検証(`ValueError): 3-D でない / NaN・Inf を含む / voxel 数が MAX_VOXELS`
(`1 << 27`)を超える。
使いどころ: `vol_watershed の地形(landscape)入力、vol_local_maxima` で
界面の峰を拾う、`vol_stretch で [0, 1]` に正規化して表示。
• 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.
• vessel_metrology — py -3.11 examples_3d/vessel_metrology.py
voxel as input)voxel_to_mips · voxel_to_mesh · signed_distance_field · to_points · sobel3d · hessian3d · curvature_maps · edt_jfa
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).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.