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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