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Development of a deep learning method for CT-free attenuation correction for an ultra-long axial field of view PET scanner

S Xue,KP Bohn, R Guo,H Sari,M Viscione,A Rominger,B Li,K Shi

59. Jahrestagung der Deutschen Gesellschaft für NuklearmedizinNuklearmedizin - NuclearMedicine（2021）

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Abstract
Ziel/Aim The possibility of reduced ionization dose of ultra-high-sensitivity total-body PET makes attenuation computed tomography (CT) a critical radiation burden in clinical applications. Artificial intelligence has shown the potential to generate PET images from non-attenuation corrected PET images. Our aim in this work is to develop a CT-free attenuation correction (AC) for an ultra-long field of view (FOV) PET scanner.
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Key words
attenuation correction,PET/CT,Dual-Energy CT,Imaging,Multi-Energy CT
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