Matches in SemOpenAlex for { <https://semopenalex.org/work/W3216421685> ?p ?o ?g. }
- W3216421685 abstract "While Computed Tomography (CT) reconstruction from X-ray sinograms is necessary for clinical diagnosis, iodine radiation in the imaging process induces irreversible injury, thereby driving researchers to study sparse-view CT reconstruction, that is, recovering a high-quality CT image from a sparse set of sinogram views. Iterative models are proposed to alleviate the appeared artifacts in sparse-view CT images, but the computation cost is too expensive. Then deep-learning-based methods have gained prevalence due to the excellent performances and lower computation. However, these methods ignore the mismatch between the CNN's textbf{local} feature extraction capability and the sinogram's textbf{global} characteristics. To overcome the problem, we propose textbf{Du}al-textbf{Do}main textbf{Trans}former (textbf{DuDoTrans}) to simultaneously restore informative sinograms via the long-range dependency modeling capability of Transformer and reconstruct CT image with both the enhanced and raw sinograms. With such a novel design, reconstruction performance on the NIH-AAPM dataset and COVID-19 dataset experimentally confirms the effectiveness and generalizability of DuDoTrans with fewer involved parameters. Extensive experiments also demonstrate its robustness with different noise-level scenarios for sparse-view CT reconstruction. The code and models are publicly available at https://github.com/DuDoTrans/CODE" @default.
- W3216421685 created "2021-12-06" @default.
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- W3216421685 date "2021-11-21" @default.
- W3216421685 modified "2023-09-27" @default.
- W3216421685 title "DuDoTrans: Dual-Domain Transformer Provides More Attention for Sinogram Restoration in Sparse-View CT Reconstruction" @default.
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- W3216421685 doi "https://doi.org/10.48550/arxiv.2111.10790" @default.
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