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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Detalles Bibliográficos
Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2019
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6815316/
https://www.ncbi.nlm.nih.gov/pubmed/31655943
http://dx.doi.org/10.1186/s41747-019-0120-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6815316/
https://www.ncbi.nlm.nih.gov/pubmed/31655943
http://dx.doi.org/10.1186/s41747-019-0120-7

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