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.
IEEE TMI 33(12) (2014) 2332–2341
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.IV 1years
2019 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
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.