Concordance of Computed Tomography Regional Body Composition Analysis Using a Fully Automated Open-Source Neural Network versus a Reference Semi-Automated Program with Manual Correction

Concordance of Computed Tomography Regional Body Composition Analysis Using a Fully Automated Open-Source Neural Network versus a Reference Semi-Automated Program with Manual Correction

Quick, efficient, fully automated open-source programs to segment muscle and adipose tissues from computed tomography (CT) images would be a great contribution to body composition research. This study examined the concordance of cross-sectional areas (CSA) and densities for muscle, visceral adipose...

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Bibliographic Details
Main Authors: Sandra L. Gomez-Perez, Yanyu Zhang, Cecily Byrne, Connor Wakefield, Thomas Geesey, Joy Sclamberg, Sarah Peterson
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Sensors
Subjects:
computed tomography
body composition
validation
agreement
adipose tissue
muscle
Online Access:https://www.mdpi.com/1424-8220/22/9/3357

Internet

https://www.mdpi.com/1424-8220/22/9/3357

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