A deep learning method for total-body dynamic PET imaging with dual-time-window protocols.
Purpose: Prolonged scanning durations are one of the primary barriers to the widespread clinical adoption of dynamic Positron Emission Tomography (PET). In this paper, we developed a deep learning algorithm that capable of predicting dynamic images from dual-time-window protocols, thereby shortening...
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 52; no. 4; pp. 1448 - 1460 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Mar2025
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| Acceso en línea: | Ver este registro en EBSCOhost |