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Deep learning-based filling of incomplete sinograms from low-cost, long axial field-of-view PET scanners with inter-detector gaps 2023 (English)In: The international networking symposiumon artificial intelligence and informatics in nuclear medicine: Program book, University Medical Center Groningen , 2023, p. 59-59Conference paper, Oral presentation with published abstract (Refereed)

Place, publisher, year, edition, pages

University Medical Center Groningen , 2023. p. 59-59

Keywords [en]

positron emission tomography (PET), sparse PET, deep learning - artificial intelligence, residual U-net, gap filling, long axial field of view PET, total body PET

National Category

Medical Imaging Computational Mathematics Computer graphics and computer vision

Research subject

Mathematical Statistics

Identifiers

URN: urn:nbn:se:umu:diva-224909OAI: oai:DiVA.org:umu-224909DiVA, id: diva2:1860574

Conference

International Symposium on Artificial Intelligence and Informatics in Nuclear Medicine, Groningen, Netherlands, October 9-11, 2023.

Part of project

Statistical modelling and intelligent data sampling in MRI and PET measurements for cancer therapy assessment, Swedish Research Council

Funder

Swedish Research Council, 340-2013-5342Available from: 2024-05-24 Created: 2024-05-24 Last updated: 2025-02-09Bibliographically approved

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No full text in DiVA

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Authority records

Leffler, KlaraAxelsson, Jan

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Leffler, KlaraAxelsson, Jan

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Department of Mathematics and Mathematical StatisticsDepartment of Diagnostics and Intervention

On the subject

Medical ImagingComputational MathematicsComputer graphics and computer vision

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