EMATA: a toolbox for the automatic extraction and modeling of arterial inputs for tracer kinetic analysis in [18F]FDG brain studies
EMATA proved adaptability to different datasets characteristics and the ability to provide arterial input functions that can be used for reliable PET quantitative analysis.
Authors
- Manu S. Goyal (ORCID: https://orcid.org/0000-0003-1970-4270)
- Andrea Bettinelli (ORCID: https://orcid.org/0000-0002-3539-3540)
- Mattia De Francisci (ORCID: https://orcid.org/0000-0001-5137-2697)
- Andrei G. Vlassenko (ORCID: https://orcid.org/0000-0002-4776-4855)
- Diego Cecchin (ORCID: https://orcid.org/0000-0001-7956-1924)
- Alessandra Bertoldo (ORCID: https://orcid.org/0000-0002-6262-6354)
- Tommaso Volpi (ORCID: https://orcid.org/0000-0002-5451-6710)
- Erica Silvestri (ORCID: https://orcid.org/0000-0002-1853-0777)
Institutions
- University of Padua (IT)
- Yale University (US)
- Mallinckrodt (United States) (US)
- Istituto Oncologico Veneto (IT)
Publication Details
- Journal
- EJNMMI Physics
- Published
- 2024-12-24
- DOI
- https://doi.org/10.1186/s40658-024-00707-2
- Citations
- 2
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- National Institutes of Health