tm_sart_reconstruct — 2D tomography op

• Data kinds: image → image

• Call: fullseye.apply(img, "tm_sart_reconstruct", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

Algebraic reconstruction: run a few SART/SIRT sweeps on the input sinogram (rows = angles). `a sets the iteration count (round(1+a*4) -> 1..5), b sets the relaxation factor (0.05 + b*0.35). Uses skimage.transform.iradon_sart` when available, else a self-contained NumPy SIRT (project -> residual -> weighted back-projection) loop. Output refit to HxW.

Detailed usage guide

• gallery2d_physics_alife_3d family guide

References (sample data, literature)

• 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.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• gallery2d_physics_alife_3d — py -3.11 examples/gallery2d_physics_alife_3d.py

Ops the type connects to (they accept image as input)

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

Same category (tomography)

tm_radon_forward · tm_fbp_reconstruct · tm_backproject_unfiltered · tm_sinogram_denoise

*Provenance: ops.py — 2D 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.