ArticleSIAM journal on imaging sciences2021
On Learned Operator Correction in Inverse Problems.
Article in SIAM journal on imaging sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- Machine-learning-enhanced image reconstruction in optical tomography using the Monte Carlo method for light transport.Journal of biomedical optics · 2026Article
- Diffuse optical tomography of the brain: effects of inaccurate baseline optical parameters and refinements using learned post-processing.Biomedical optics express · 2024Article
- Quantitative photoacoustic tomography: modeling and inverse problems.Journal of biomedical optics · 2024Review
- A generalization of the maximum likelihood expectation maximization (MLEM) method: Masked-MLEM.Physics in medicine and biology · 2023Article
- Structural engineering from an inverse problems perspective.Proceedings. Mathematical, physical, and engineering sciences · 2022Review
- Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems.IEEE transactions on computational imaging · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
We discuss the possibility of learning a data-driven explicit model correction for inverse problems and whether such a model correction can be used within a variational framework to obtain regularized reconstructions. This paper discusses the conceptual difficulty of learning such a forward model correction and proceeds to present a possible solution as a forward-adjoint correction that explicitly corrects in both data and solution spaces. We then derive conditions under which solutions to the variational problem with a learned correction converge to solutions obtained with the correct operator. The proposed approach is evaluated on an application to limited view photoacoustic tomography and compared to the established framework of the Bayesian approximation error method.
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Registered trials
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