Abstract #0939

MRI-based Direct PET Attenuation Correction Using Cross-modality Attention Network for Combined PET/MRI

Xiaofeng Yang¹, Yang Lei¹, Tonghe Wang², Sagar Mandava³, Tian Liu⁴, Jonathon Nye¹, and Hui Mao¹

¹Emory University, Atlanta, GA, United States, ²Memorial Sloan Kettering Cancer Center, New York, NY, United States, ³GE Healthcare, Atlanta, GA, United States, ⁴Icahn School of Medicine at Mount Sinai, New York, NY, United States

Synopsis

Keywords: PET/MR, Machine Learning/Artificial IntelligenceThis study aims to develop an efficient and clinically applicable deep-learning method using routine T1-weighted MRI and non-AC PET to directly synthesize high-quality attenuation-corrected PET without the need of an attenuation coefficient map for simultaneous PET/MRI.

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