Physically informed deep neural networks for metabolite-corrected plasma input function estimation in dynamic PET imaging-Reference-Cited by-同舟云学术

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Physically informed deep neural networks for metabolite-corrected plasma input function estimation in dynamic PET imaging

Published:2024-11 Issue: Volume:256 Page:108375
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Ferrante Matteo^ORCID,Inglese Marianna^ORCID,Brusaferri Ludovica,Whitehead Alexander C.^ORCID,Maccioni Lucia^ORCID,Turkheimer Federico E.^ORCID,Nettis Maria A.,Mondelli Valeria,Howes Oliver,Loggia Marco L.^ORCID,Veronese Mattia^ORCID,Toschi Nicola

Funder

Horizon 2020 European Innovation Council Fast Track to Innovation

European Innovation Council

Publisher

Elsevier BV

Reference45 articles.

1. Positron Emission Tomography: Basic Sciences;Bailey,2005

2. Kinetic modeling in positron emission tomography;Schmidt;Q. J. Nucl. Med.,2002

3. Comparison of image-derived and arterial input functions for estimating the rate of glucose metabolism in therapy-monitoring 18F-FDG PET studies;de Geus-Oei;J. Nucl. Med.,2006

4. Quantitative assessment of dynamic PET imaging data in cancer imaging;Muzi;Magn. Reson. Imaging,2012

5. Standards for PET image acquisition and quantitative data analysis;Boellaard;J. Nucl. Med.,2009

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