LION.reconstructorsΒΆ

LION image reconstructors.

Modules

ForwardReconstructor(operator[, model, ...])

Reconstruct with a model's forward pass, as its solvers train it (LION.optimizers.LIONsolver.model_forward): image-domain models (e.g. FBPConvNet) get a reconstruction first (the operator's default, FDK for CT, or the model's initial_reconstruction), sinogram-domain models (e.g. LPD) the measurements; with the model's normalisation (its set_normalisation(), saved with it), the input is normalised and the output mapped back.

LIONreconstructor

The base class of reconstructors: methods that reconstruct with a trained model (e.g. a denoiser as a prior, a learned regulariser) inside an algorithm.

LearnedRegularizerReconstructor(operator[, ...])

Reconstruct by minimising a variational energy with a learned regulariser,

PnP(operator[, model, parameters])

Plug-and-Play reconstruction with a denoiser (model) as the prior.