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Simulated nanoCT Datasets

Name: Simulated nanoCT Datasets
Keywords: operator inexactness, nano-CT, computed tomography

Research datakeyboard_double_arrow_right Dataset 01 Sep 2023 English Publisher:ZenodoFunded by:DFG | Pi³ : Parameter Identific..., DFG | unidentified

Authors: Lütjen, Tom; Schönfeld, Fabian; Oberacker, Alice; Leuschner, Johannes; Schmidt, Maximilian; Wald, Anne; Kluth, Tobias;

doi: 10.5281/zenodo.8123499 , 10.5281/zenodo.8123498

Simulated nanoCT Datasets

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Abstract

Simulated parallel-beam and fan-beam nano-CT datasets with per-angle random phantom shifts and rotations. The dataset generation is described in the paper Learning-based approaches for reconstructions with inexact operators in nanoCT applications. Code to use the data is available at https://gitlab.informatik.uni-bremen.de/inn4ip/cond-inn4nanoct (in particular the module src/learned_reco/data.py).

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Keywords

operator inexactness, nano-CT, computed tomography

1 Research products, page 1 of 1

Learning-Based Approaches for Reconstructions With Inexact Operators in nanoCT Applications
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