Automated Quantitative Image-Derived Input Function for the Estimation of Cerebral Blood Flow Using Oxygen-15-Labelled Water on a Long-Axial Field-of-View PET/CT Scanner

The accurate estimation of the tracer arterial blood concentration is crucial for reliable quantitative kinetic analysis in PET. In the current work, we demonstrate the automatic extraction of an image-derived input function (IDIF) from a CT AI-based aorta segmentation subsequently resliced to a dyn...

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主要な著者:	Thomas Lund Andersen, Flemming Littrup Andersen, Bryan Haddock, Sverre Rosenbaum, Henrik Bo Wiberg Larsson, Ian Law, Ulrich Lindberg
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2024-07-01
シリーズ:	Diagnostics
主題:	image-derived input function kinetic modelling arterial input function perfusion positron emission tomography long-axial field-of-view scanner
オンライン･アクセス:	https://www.mdpi.com/2075-4418/14/15/1590
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