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Noise suppression in photon-counting computed tomography using unsupervised Poisson flow generative models.

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Title: Noise suppression in photon-counting computed tomography using unsupervised Poisson flow generative models.
Authors: Hein, Dennis1,2, dhein@kth.se, Holmin, Staffan3,4, Szczykutowicz, Timothy5, Maltz, Jonathan S.6, Danielsson, Mats1,2, Wang, Ge7, Persson, Mats1,2
Source: Visual Computing for Industry, Biomedicine & Art; 9/23/2024, Vol. 7 Issue 1, p1-14, 14p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 179815164
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=179815164
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      – Type: doi
        Value: 10.1186/s42492-024-00175-6
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      – Code: eng
        Text: English
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      – TitleFull: Noise suppression in photon-counting computed tomography using unsupervised Poisson flow generative models.
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            NameFull: Hein, Dennis
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            NameFull: Danielsson, Mats
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            – D: 23
              M: 09
              Text: 9/23/2024
              Type: published
              Y: 2024
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