Decentralized collaborative multi-institutional PET attenuation and scatter correction using federated deep learning.

Purpose: Attenuation correction and scatter compensation (AC/SC) are two main steps toward quantitative PET imaging, which remain challenging in PET-only and PET/MRI systems. These can be effectively tackled via deep learning (DL) methods. However, trustworthy, and generalizable DL models commonly r...

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Publicado en:	European Journal of Nuclear Medicine & Molecular Imaging Vol. 50; no. 4; pp. 1034 - 1051
Autores principales:	Shiri, Isaac, Vafaei Sadr, Alireza, Akhavan, Azadeh, Salimi, Yazdan, Sanaat, Amirhossein, Amini, Mehdi, Razeghi, Behrooz, Saberi, Abdollah, Arabi, Hossein, Ferdowsi, Sohrab, Voloshynovskiy, Slava, Gündüz, Deniz, Rahmim, Arman, Zaidi, Habib
Formato:	Journal Article
Publicado:	Springer Nature Mar2023
Acceso en línea:	Ver este registro en EBSCOhost