End-to-end automated body composition analyses with integrated quality control for opportunistic assessment of sarcopenia in CT

OBJECTIVES: To develop a pipeline for automated body composition analysis and skeletal muscle assessment with integrated quality control for large-scale application in opportunistic imaging. METHODS: First, a convolutional neural network for extraction of a single slice at the L3/L4 lumbar level was...

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Detalles Bibliográficos
Autores principales: Nowak, Sebastian, Theis, Maike, Wichtmann, Barbara D., Faron, Anton, Froelich, Matthias F., Tollens, Fabian, Geißler, Helena L., Block, Wolfgang, Luetkens, Julian A., Attenberger, Ulrike I., Sprinkart, Alois M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Imaging Informatics and Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9038788/
https://www.ncbi.nlm.nih.gov/pubmed/34595539
http://dx.doi.org/10.1007/s00330-021-08313-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9038788/
https://www.ncbi.nlm.nih.gov/pubmed/34595539
http://dx.doi.org/10.1007/s00330-021-08313-x

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