Quantitative evaluation of a deep learning-based framework to generate whole-body attenuation maps using LSO background radiation in long axial FOV PET scanners.
Purpose: Attenuation correction is a critically important step in data correction in positron emission tomography (PET) image formation. The current standard method involves conversion of Hounsfield units from a computed tomography (CT) image to construct attenuation maps (µ-maps) at 511 keV. In thi...
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 49; no. 13; pp. 4490 - 4503 |
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| Autores principales: | , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Nov2022
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| Acceso en línea: | Ver este registro en EBSCOhost |