Fully automated convolutional neural network-based affine algorithm improves liver registration and lesion co-localization on hepatobiliary phase T1-weighted MR images

BACKGROUND: Liver alignment between series/exams is challenged by dynamic morphology or variability in patient positioning or motion. Image registration can improve image interpretation and lesion co-localization. We assessed the performance of a convolutional neural network algorithm to register cr...

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Pubblicato in:Eur Radiol Exp
Autori principali: Hasenstab, Kyle A., Cunha, Guilherme Moura, Higaki, Atsushi, Ichikawa, Shintaro, Wang, Kang, Delgado, Timo, Brunsing, Ryan L., Schlein, Alexandra, Bittencourt, Leornado Kayat, Schwartzman, Armin, Fowler, Katie J., Hsiao, Albert, Sirlin, Claude B.
Natura: Artigo
Lingua:Inglês
Pubblicazione: Springer International Publishing 2019
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Original Article
Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC6815316/
https://ncbi.nlm.nih.gov/pubmed/31655943
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s41747-019-0120-7
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