Fully-automated Segmentation of Muscle Measurement on CT in Detecting Central Sarcopenia: A Trend of Standardization
Author:
Publisher
Elsevier BV
Subject
Radiology Nuclear Medicine and imaging
Reference8 articles.
1. A machine learning algorithm to estimate sarcopenia on abdominal CT;Burns;Acad Radiol,2020
2. Sarcopenia: current concepts and imaging implications;Boutin;AJR Am J Roentgenol,2015
3. Criteria for clinically relevant weakness and low lean mass and their longitudinal association with incident mobility impairment and mortality: the Foundation for the National Institutes of Health (FNIH) sarcopenia project;McLean;J Gerontol A Biol Sci Med Sci,2014
4. Recent issues on body composition imaging for sarcopenia evaluation;Lee;Korean J Radiol,2019
5. Prognostic significance of sarcopenia in patients with unresectable advanced esophageal cancer;Onishi;J Clin Med,2019
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