Measured Walnut

examples/walnut_reconstruction.py reconstructs a measured walnut from 240 cone-beam projections on a full circular orbit. The data are from Meaney 2022 (Zenodo 6986012, CC BY 4.0; see examples/data/NOTICE). The scan geometry is passed to Projector as explicit per-view tensors, the same way as a calibrated trajectory.

Run it

Run the commands from the root of a source checkout; pip install diffct does not install the examples/ directory. See the “From source” tab in Installation. --figure needs Matplotlib: pip install matplotlib.

python examples/walnut_reconstruction.py --figure walnut.png
python examples/walnut_reconstruction.py --size 512 --devices 0 1 2 3

The figure shows axial and coronal centre slices. The reconstructions are:

• FDK with a Hann window.

• SIRT (200 iterations).

• CGLS (20 iterations).

• TV-regularized least squares (300 Adam steps, weight 0.3).

Use --algorithms with no values to run FDK only. Use --window to change the FDK filter.

Simulated helical scan

--save-volume stores the FDK volume scaled to [0, 1]. Use it as the phantom for a simulated helical scan:

python examples/walnut_reconstruction.py --algorithms --save-volume walnut256.npy
python examples/iterative_reconstruction.py --size 256 --views 720 --trajectory helical \
    --noise 0.01 --phantom walnut256.npy --figure helical.png