sinogram_design — TOMOGRAPHY layout op

• 資料種類:無 → table(僅由參數決定的運算子 —— 不接受影像或資料輸入)

• 呼叫: import fullseye as fs; fs.ledger.sinogram_design(n_angles=180, n_detectors=None, size=256, detector_pitch_mm=1.0, span_deg=180.0)(要直接呼叫實作,import tomography; tomography.sinogram_design(n_angles=180, n_detectors=None, size=256, detector_pitch_mm=1.0, span_deg=180.0);從台帳取用則 opstomography.get("sinogram_design"))

用法

這套掃描幾何能解析什麼、不能解析什麼 —— 在動手之前。

> 以下的詳細說明為原文 —— 摘要與標題已翻譯。

The axial counterpart of visiondesign.imaging_budget and of interferometry.csi_design: no data goes in, only the geometry, and what comes out are the limits that the geometry has already decided.

Returns a dict with, among others:

• resolvable_feature_mm — 2 * pitch: two detector samples per cycle is the Nyquist floor, and no reconstruction algorithm recovers a detail finer than the detector saw.

• views_for_full_sampling — ceil(pi/2 * n_detectors), the classical matching of angular to radial sampling (VIEWS_PER_DETECTOR).

• undersampling_factor — that number over n_angles. 1.0 or below is a fully sampled scan. Above it you are doing sparse-view CT on purpose and the reconstruction algorithm has to make up the difference; the measured cost is in this module's docstring and in the test suite's break table.

• streak_free_radius_px — 1 / d(theta) with d(theta) in radians: the radius, in pixels, at which the *azimuthal* sample spacing between neighbouring views (r * d(theta)) grows past one sample. Outside it, filtered back-projection lays down visible streaks. For 180 views over 180 degrees this is 57.3 px, i.e. a 256-px phantom is already streaking at its corners. It does not depend on the detector pitch: the radius is quoted in the same unit the sample spacing is, so the pitch cancels (pitch / d(theta) is the same radius in millimetres, which is what an earlier version returned under the pixel label — 28.6 "px" at 0.5 mm, 114.6 at 2 mm, for a geometry whose streak radius had not changed).

• sinogram_bytes / elements — what you are about to allocate.

• verdict — "fully sampled" / "sparse view".

:param n_angles: planned number of views. :param n_detectors: planned detector bins; None -> enough to cover the

diagonal of a *size* x *size* image.

:param size: reconstruction grid side in pixels. :param detector_pitch_mm: physical detector bin spacing. :param span_deg: angular range of the scan. :returns: dict of floats / ints / str. :raises ValueError: on non-int counts, non-positive pitch or span.

參考(範例資料、文獻)

• 範例資料目錄(下載 URL / 授權) —— 2-D 用 skimage.data(BSD/公有領域)加合成圖,3-D 給出真實資料源(Stanford/PDS 等)的下載 URL。

• 運算子來歷與參考文獻 —— 該運算子族所依據的研究/方法出處。

• 演算法的正典(作者、年份)與用途見上面的族使用指南。

可執行的範例(實際呼叫該運算子並已驗證的樣例)

• ct_reconstruction — py -3.11 examples/ct_reconstruction.py

• tomography_reconstruct — py -3.11 examples/tomography_reconstruct.py

型別可銜接的下一個運算子(可接受 table 作為輸入)

—

同類別(layout)

projection_angles


*Provenance: tomography.py — TOMOGRAPHY 運算子登記表。本條目由 tools/opdocs.py md 自動產生(請勿手動編輯)。*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.