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Abstract #1776

Robust PET attenuation correction for PET/MR using joint estimation with MR-based priors: application to whole-body clinical TOF PET/MR data

Sangtae Ahn1, Lishui Cheng1, Dattesh Shanbhag2, and Florian Wiesinger3

1GE Global Research, Niskayuna, NY, United States, 2GE Global Research, Bangalore, India, 3GE Global Research, Munich, Germany

PET attenuation correction is critical to accurate PET quantitation. For hybrid PET/MR imaging, MR-based attenuation correction (MRAC) has challenges in implants, internal air, bones and lung regions where MR signals are low. To address the challenges and improve robustness and accuracy of MRAC, a joint estimation algorithm with MR-based priors is implemented where prior weights are spatially modulated, providing great flexibility to users. The JE algorithm was applied to whole-body clinical TOF PET/MR data and it was demonstrated that the algorithm can recover the attenuation of implants, abdominal air and lungs in a robust way.

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