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. 2024 Feb 6;17(1):24–46. doi: 10.1007/s12194-024-00780-3

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© The Author(s) 2024, corrected publication 2024

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 5 — Examples of the denoised brain ¹⁸F-florbetapir PET images by unsupervised learning approaches. From left to right, the sample images showing the MR, standard-count PET, noisy PET, and denoised PET images corresponding to the Gaussian filter (GF), image-guided filter (IGF), DIP, MR-DIP (CDIP), and MR-guided deep decoder (GDD).

© 2021 Elsevier. Reprinted with permission from Onishi et al. [143]