Rationale and Objectives To assess whether a fully-automated deep learning system can
accurately detect and analyze truncal musculature at multiple lumbar vertebral levels and …

BACKGROUND. Sarcopenia is associated with adverse clinical outcomes. CT-based
skeletal muscle measurements for sarcopenia assessment are most commonly performed at …

Objective: To investigate a fully automated abdominal CT-based muscle tool in a large adult
screening population. Methods: A fully automated validated muscle segmentation algorithm …

Rationale and Objectives To develop and evaluate an automated machine learning (ML)
algorithm for segmenting the paraspinous muscles on chest computed tomography (CT) …

Background Quantification of abdominal muscle mass by cross-sectional imaging has been
increasingly used to diagnose sarcopenia; however, the technical method for quantification …

Background Sarcopenia is defined as the loss of skeletal muscle mass and function
associated with aging. Muscle mass can be reliably and accurately quantified using clinical …

Measurements of skeletal muscle cross-sectional area, index, and radiation attenuation
utilizing clinical computed tomography (CT) scans are used in assessments of sarcopenia …

Muscle ultrasound is an emerging tool for diagnosing sarcopenia. This review aims to
summarize the current knowledge on the diagnostic test accuracy of ultrasound for the …

Background Low skeletal muscle quantified using computed tomography (CT) scans is
associated with morbidity and mortality among cancer patients. However, existing methods …

Body composition on chest CT scans encompasses a set of important imaging biomarkers.
This study developed and validated a fully automated analysis pipeline for multi–vertebral …