Development and Validation of a Deep Learning System for Segmentation of Abdominal Muscle and Fat on Computed Tomography

OBJECTIVE: We aimed to develop and validate a deep learning system for fully automated segmentation of abdominal muscle and fat areas on computed tomography (CT) images. MATERIALS AND METHODS: A fully convolutional network-based segmentation system was developed using a training dataset of 883 CT sc...

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Detalles Bibliográficos
Autores principales: Park, Hyo Jung, Shin, Yongbin, Park, Jisuk, Kim, Hyosang, Lee, In Seob, Seo, Dong-Woo, Huh, Jimi, Lee, Tae Young, Park, TaeYong, Lee, Jeongjin, Kim, Kyung Won
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Radiology 2020
Materias:
Gastrointestinal Imaging
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6960305/
https://www.ncbi.nlm.nih.gov/pubmed/31920032
http://dx.doi.org/10.3348/kjr.2019.0470

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6960305/
https://www.ncbi.nlm.nih.gov/pubmed/31920032
http://dx.doi.org/10.3348/kjr.2019.0470

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