sirt_reconstruct — TOMOGRAPHY ct_scan op

• 数据种类:projstack × ctgeometry → voxel

• 调用: import fullseye as fs; fs.ledger.sirt_reconstruct(projections, geometry, n_iter=50, relaxation=1.0, initial=None, nonnegative=True, device='auto', on_iter=None)(要直接调用实现,import ctscan; ctscan.sirt_reconstruct(projections, geometry, n_iter=50, relaxation=1.0, initial=None, nonnegative=True, device='auto', on_iter=None);从台账取用则 opstomography.get("sirt_reconstruct"))

• GPU:无(仅 CPU 参考实现)

用法

SIRT:同时使用全部视角,x <- x + lam C A^T R (p - A x)。

> 以下的详细说明为原文 —— 摘要与标题已翻译。

R and C are the inverse row and column sums of A. With the matched pair of this family it minimises a weighted least-squares error, and it needs no formula, so it is the route for tomosynthesis, few views and limited angle.

:param projections: (view, V, U) line integrals. :param geometry: dict from ct_scan_geometry. :param n_iter: iterations, 1 .. 5000. :param relaxation: step lam, (0, 2). :param initial: starting volume; None gives zeros. :param nonnegative: clip to >= 0 after each iteration. :param device: "auto", "cpu" or "cuda". :param on_iter: optional on_iter(iteration, volume) for a convergence curve;

returning a boolean True (bool or numpy.bool_) stops after

that iteration; any other return value (None, numbers, dicts,

arrays) is ignored.

:returns: (Z, Y, X) float volume. :raises ValueError: on a shape that disagrees with the geometry or a relaxation

outside (0, 2). Empty input (projections with 0 elements) raises

ValueError.

The default 50 iterations is not converged. SIRT moves slowly. On consistent data (24^3 Shepp-Logan, cone, 20 views) the relative residual is 0.0318 at 50 iterations and 0.0087 at 200, and the nRMS to the truth drops from 0.0407 to 0.0232 (43 %); on the measured walnut (fan, 50 views) the RMSE to the reference is 0.0055 /mm at 60 iterations and 0.0036 at 400 (2026-11-09 audit). Comparing methods at the defaults makes SIRT look worse than it is. Choose n_iter from a curve: on_iter can compute the residual |A x - p| / |p| (ct_forward_project) or the error on held-out views, and return True once its relative change falls below e.g. 1e-3. With noisy data the error to the truth reaches a minimum and then rises again (semi-convergence), so the residual alone is not a stopping rule there.

参考(示例数据、文献)

• 示例数据目录(下载 URL / 许可证) —— 2-D 用 skimage.data(BSD/公有领域)加合成图,3-D 给出真实数据源(Stanford/PDS 等)的下载 URL。

• 算子来历与参考文献 —— 该算子族所依据的研究/方法出处。

• 算法的正典(作者、年份)与用途见上面的族使用指南。

可运行的示例(实际调用该算子并已验证的样例)

• ct_scan_modes — py -3.11 examples/ct_scan_modes.py

• poc_ct_casting_sparse_views — py -3.11 examples/poc_ct_casting_sparse_views.py

• poc_real_walnut_cbct — py -3.11 examples/poc_real_walnut_cbct.py

类型可衔接的下一个算子(可接受 voxel 作为输入)

radon_volume · ct_forward_project

同类别(ct_scan)

ct_scan_geometry · shepp_logan_3d · ellipsoid_phantom · ellipsoid_projections · ct_forward_project · ct_adjoint_project · fdk_reconstruct · os_sart_reconstruct


*Provenance: ctscan.py — TOMOGRAPHY 算子登记表。本条目由 tools/opdocs.py md 自动生成(请勿手工编辑)。*

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