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- W4385543579 abstract "Inspired by recent usage of Deep Image Prior (DIP) in the field of MRI that utilizes a powerful low-level image prior from a neural network architecture itself without any training dataset, we conduct k-space extrapolation using the deep prior for Gibbs-ringing removal in order to build general Gibbs-ringing correction algorithm without dependency on the dataset. We further improved the existing deep prior with the addition of anti-aliasing layers. The proposed deep prior method outperformed conventional non-learning methods quantitively and qualitatively in numerical simulations and in-vivo data." @default.
- W4385543579 created "2023-08-04" @default.
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- W4385543579 date "2023-08-03" @default.
- W4385543579 modified "2023-09-27" @default.
- W4385543579 title "Gibbs-ringing Removal through Anti-aliased Deep Priors" @default.
- W4385543579 doi "https://doi.org/10.58530/2022/0956" @default.
- W4385543579 hasPublicationYear "2023" @default.
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