A multi-hypothesis CNN with a learned PET-residual loss produces pseudo-CTs that reduce PET reconstruction error at the cost of higher CT error.
In: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, Springer International Publishing (2018) 174–182
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Improved MR to CT synthesis for PET/MR attenuation correction using Imitation Learning
A multi-hypothesis CNN with a learned PET-residual loss produces pseudo-CTs that reduce PET reconstruction error at the cost of higher CT error.