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- W2807149895 abstract "Binary tomography focuses on the problem of reconstructing homogeneous objects from a small number of their projections. In many applications, incomplete projection data holds insufficient information for the correct reconstruction of the original object. In this paper, we provide an optimization based method to select the “most informative” projection set, using information of global uncertainty. Beside the projection data we assume no further knowledge of the image to be reconstructed. Still, we achieve approximately as accurate reconstruction results, as it is possible to gain with a former method that uses blueprint images to find the optimal set of projections. We give experimental results for validating our approach on artificial images of various structures." @default.
- W2807149895 created "2018-06-13" @default.
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- W2807149895 date "2018-01-01" @default.
- W2807149895 modified "2023-10-06" @default.
- W2807149895 title "Projection Selection for Binary Tomographic Reconstruction Using Global Uncertainty" @default.
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- W2807149895 doi "https://doi.org/10.1007/978-3-319-93000-8_1" @default.
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