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 …

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

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 …

Purpose The purpose of this study was to build and train a deep convolutional neural
networks (CNN) algorithm to segment muscular body mass (MBM) to predict muscular …

Objectives To develop a pipeline for automated body composition analysis and skeletal
muscle assessment with integrated quality control for large-scale application in opportunistic …

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

Background Muscle wasting (Sarcopenia) is associated with poor outcomes in cancer
patients. Early identification of sarcopenia can facilitate nutritional and exercise intervention …

Purpose Tracing muscle groups manually on CT to calculate body composition parameters
and diagnose sarcopenia is costly and time consuming. Artificial Intelligence (AI) provides …

Manual segmentation of muscle and adipose compartments from computed tomography
(CT) axial images is a potential bottleneck in early rapid detection and quantification of …

Sarcopenia is a muscle disease which previously was associated only with aging, but in
recent days it has been gaining more attention for its predictive value in a vast range of …