Deep-learning-derived input function in dynamic [18F]FDG PET imaging of mice

Dynamic positron emission tomography and kinetic modeling play a critical role in tracer development research using small animals. Kinetic modeling from dynamic PET imaging requires accurate knowledge of an input function, ideally determined through arterial blood sampling. Arterial cannulation in m...

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Λεπτομέρειες βιβλιογραφικής εγγραφής

Κύριοι συγγραφείς:	Samuel Kuttner, Luigi T. Luppino, Laurence Convert, Otman Sarrhini, Roger Lecomte, Michael C. Kampffmeyer, Rune Sundset, Robert Jenssen
Μορφή:	Artigo
Γλώσσα:	Inglês
Έκδοση:	Frontiers Media S.A. 2024-04-01
Σειρά:	Frontiers in Nuclear Medicine
Θέματα:	dynamic positron emission tomography (PET) small-animal PET 18F-FDG PET/CT Patlak analysis arterial input function estimation glucose metabolism deep learning
Διαθέσιμο Online:	https://www.frontiersin.org/articles/10.3389/fnume.2024.1372379/full
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