Development of a denoising convolutional neural network-based algorithm for metal artifact reduction in digital tomosynthesis for arthroplasty: A phantom study

The present study aimed to develop a denoising convolutional neural network metal artifact reduction hybrid reconstruction (DnCNN-MARHR) algorithm for decreasing metal objects in digital tomosynthesis (DT) for arthroplasty by using projection data. For metal artifact reduction (MAR), we implemented...

Descripció completa

Guardat en:
Dades bibliogràfiques
Publicat a:PLoS One
Autors principals: Gomi, Tsutomu, Sakai, Rina, Hara, Hidetake, Watanabe, Yusuke, Mizukami, Shinya
Format: Artigo
Idioma:Inglês
Publicat: Public Library of Science 2019
Matèries:
Research Article
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC6743787/
https://ncbi.nlm.nih.gov/pubmed/31518374
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0222406
Etiquetes: Afegir etiqueta
Sense etiquetes, Sigues el primer a etiquetar aquest registre!

Ítems similars