artifact op• データ種: sinogram → sinogram
• 呼び出し: import fullseye as fs; fs.ledger.ring_artifact_apply(sinogram, gain_sigma=0.02, seed=0, offsets=None) (実装を直接呼ぶなら import tomography; tomography.ring_artifact_apply(sinogram, gain_sigma=0.02, seed=0, offsets=None)、台帳から引くなら opstomography.get("ring_artifact_apply"))
検出器にビンごとのゲイン誤差を与える —— リングアーチファクトの源。
> 以下の詳細説明は原文のままです —— 要約と見出しは訳出済み。
A detector bin whose gain is g reports I = g I_true, so after the logarithm the line integral picks up a constant offset -ln g at that bin, the same at every angle. Back-projecting a constant column smears it around the rotation axis, and the reconstruction grows a ring at the radius that bin's rays are tangent to. One bad pixel, one perfect circle.
The offsets are drawn once from N(0, gain_sigma) with a fixed *seed* and applied to every row, because the whole point is that the error does not vary with angle — that is what distinguishes a ring from noise, and what makes ring_artifact_remove possible.
:param sinogram: (n_angles, n_detectors). :param gain_sigma: standard deviation of the per-bin offset, >= 0. :param seed: RNG seed; there is no None (determinism is a contract here). :param offsets: explicit (n_detectors,) offsets; overrides the random draw. :returns: (n_angles, n_detectors) float64 sinogram. :raises ValueError: on a negative sigma, a non-int seed, or an *offsets* whose
length is not the detector count.
• サンプルデータ カタログ(DL URL / ライセンス) — 2-D は skimage.data(BSD/public)+ 合成、3-D は実データ源(Stanford/PDS 等)の DL URL。
• 演算子の来歴・参考文献 — この op 族の元になった研究/手法の出典。
• アルゴリズムの正典(著者・年)と用途は上記ファミリ使い方ガイドに記載。
• ct_reconstruction — py -3.11 examples/ct_reconstruction.py
• poc_battery_ct_degradation — py -3.11 examples/poc_battery_ct_degradation.py
sinogram を入力に取れる)backproject_sinogram · filtered_backprojection · sart_reconstruct · beam_hardening_apply · beam_hardening_correct · ring_artifact_remove · metal_trace_interpolate · sinogram_center_of_rotation
artifact)beam_hardening_apply · beam_hardening_correct · ring_artifact_remove · metal_trace_interpolate
*Provenance: tomography.py — TOMOGRAPHY operator registry. この per-op ノートは tools/opdocs.py md が自動生成(手編集しない)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.