ct_scan op• Data kinds: projstack × ctgeometry → voxel
• Call: import fullseye as fs; fs.ledger.tv_reconstruct(projections, geometry, tv_weight=0.0003, n_iter=200, initial=None, nonnegative=True, device='auto', on_iter=None) (implementation को सीधे call करना हो तो import ctscan; ctscan.tv_reconstruct(projections, geometry, tv_weight=0.0003, n_iter=200, initial=None, nonnegative=True, device='auto', on_iter=None), registry से लेना हो तो opstomography.get("tv_reconstruct"))
• GPU: नहीं (केवल CPU reference implementation)
Chambolle-Pock प्राइमल-ड्यूअल विधि से टोटल-वैरिएशन पुनर्निर्माण।
> नीचे का विस्तृत विवरण मूल text में है — सारांश और headings का अनुवाद हो चुका है।
Solves min 0.5 ||A x - p||^2 + w ||grad x||_1 with x >= 0, in the form Sidky, Jorgensen & Pan 2012 give for CT. The prior says that the object is piecewise constant, which is what lets it fill data that was never measured: few views and limited angle. On an object that is not piecewise constant it paints the same flat patches, so a low residual here is not evidence of truth.
*tv_weight* is in units of ||A||^2 times the volume scale, so that one value behaves alike across grid sizes.
:param projections: (view, V, U) line integrals. :param geometry: dict from ct_scan_geometry. :param tv_weight: strength of the prior, >= 0. :param n_iter: primal-dual iterations, 1 .. 5000. :param initial: starting volume; None gives zeros. :param nonnegative: enforce x >= 0. :param device: "auto", "cpu" or "cuda". :param on_iter: optional on_iter(iteration, volume); returning a boolean
True (bool or numpy.bool_) stops after that iteration, any other
return value is ignored (same rule as sirt_reconstruct).
:returns: (Z, Y, X) float volume. :raises ValueError: on a shape that disagrees with the geometry or a negative
weight. Empty input (projections with 0 elements) raises ValueError.
• Sample data catalog (DL URL / license) — 2-D के लिए skimage.data (BSD/public) + synthetic, 3-D के लिए real data sources (Stanford/PDS आदि) के DL URL।
• Operators का स्रोत और संदर्भ — इस op family के मूल research/methods के स्रोत।
• Algorithm का मानक स्रोत (लेखक, वर्ष) और उपयोग ऊपर की family usage guide में दिए गए हैं।
• 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
voxel को input के रूप में लेते हैं)radon_volume · ct_forward_project
ct_scan)ct_scan_geometry · shepp_logan_3d · ellipsoid_phantom · ellipsoid_projections · ct_forward_project · ct_adjoint_project · fdk_reconstruct · sirt_reconstruct
*Provenance: ctscan.py — TOMOGRAPHY operator registry. यह per-op note tools/opdocs.py md से अपने-आप generate होता है (हाथ से edit न करें)।*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.