We evaluated the accuracy of a deep learning-based PET/MR attenuation correction (AC) method with vendor-provided high-resolution Dixon in- and opp-phase images as inputs (DL-HiRes). We found that the DL-HiRes AC method significantly outperformed the vendor-provided skull model AC method for both 16-channel head-neck coil and 32-channel head coil (p<0.001). Moreover, the DL-HiRes method had similar AC accuracy using different head coils.
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Ying et al. (2024) studied this question.
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