Deep Learning for Multi-Tissue Segmentation and Fully Automatic Personalized Biomechanical Models from BACPAC Clinical Lumbar Spine MRI

STUDY DESIGN: In vivo retrospective study of fully automatic quantitative imaging feature extraction from clinically acquired lumbar spine magnetic resonance imaging (MRI). OBJECTIVE: To demonstrate the feasibility of substituting automatic for human-demarcated segmentation of major anatomic structu...

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Detalles Bibliográficos
Autores principales: Hess, Madeline, Allaire, Brett, Gao, Kenneth T, Tibrewala, Radhika, Inamdar, Gaurav, Bharadwaj, Upasana, Chin, Cynthia, Pedoia, Valentina, Bouxsein, Mary, Anderson, Dennis, Majumdar, Sharmila
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Original Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10403305/
https://www.ncbi.nlm.nih.gov/pubmed/36315069
http://dx.doi.org/10.1093/pm/pnac142

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10403305/
https://www.ncbi.nlm.nih.gov/pubmed/36315069
http://dx.doi.org/10.1093/pm/pnac142

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