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Published November 2024 | Version v1
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Physically informed deep neural networks for metabolite-corrected plasma input function estimation in dynamic PET imaging

Authors/Creators

  • 1. ROR icon University of Rome Tor Vergata
  • 2. ROR icon Imperial College London
  • 3. ROR icon London South Bank University
  • 4. King's College London
  • 5. King's College London Institute of Psychiatry Psychology and Neuroscience
  • 6. ROR icon Hammersmith Hospital
  • 7. ROR icon Harvard Medical School
  • 8. University of Padova

Description

Ferrante, M., Inglese, M., Brusaferri, L., Whitehead, A. C., Maccioni, L., Turkheimer, F. E., ... & Toschi, N. (2024). Physically informed deep neural networks for metabolite-corrected plasma input function estimation in dynamic PET imaging. Computer methods and programs in biomedicine, 256, 108375. https://doi.org/10.1016/j.cmpb.2024.108375

Other (En)

This work is supported and funded by: NEXTGENERATIONEU (NGEU); the Ministry of University and Research (MUR); the National Recovery and Resilience Plan (NRRP); project MNESYS (PE0000006, to NT) - A Multiscale integrated approach to the study of the nervous system in health and disease (DN. 1553 11.10.2022); the MUR-PNRR M4C2I1.3 PE6 project PE00000019 Heal Italia (to NT); the NATIONAL CENTRE FOR HPC, BIG DATA AND QUANTUM COMPUTING, within the spoke “Multiscale Modeling and Engineering Applications” (to NT); the European Innovation Council (Project CROSSBRAIN - Grant Agreement 101070908, Project BRAINSTORM - Grant Agreement 101099355); the Horizon 2020 research and innovation Programme (Project EXPERIENCE - Grant Agreement 101017727). Matteo Ferrante is a Ph.D. student enrolled in the National PhD in Artificial Intelligence, XXXVII cycle, course on Health and Life Sciences, organized by Università Campus Bio-Medico di Roma.

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Additional details

Identifiers

DOI
10.1016/j.cmpb.2024.108375

Funding

European Commission
CROSSBRAIN - Distributed and federated cross-modality actuation through advanced nanomaterials and neuromorphic learning 101070908
European Commission
EXPERIENCE - The “Extended-Personal Reality”: augmented recording and transmission of virtual senses through artificial-IntelligENCE 101017727
European Commission
BRAINSTORM - Wireless deep BRAIN STimulation thrOugh engineeRed Multifunctinal nanomaterials 101099355