Obesity is the most extended metabolic alteration worldwide increasing the risk for the
development of cardiometabolic alterations such as type 2 diabetes, hypertension, and …

Background and aims Obesity is a chronic disease which can cause severe metabolic
disorders. Machine learning (ML) techniques, especially deep learning (DL), have proven to …

Abstract Objective Three‐dimensional (3D) imaging systems are increasingly being used in
health care settings for quantifying body size and shape. The potential exists to provide …

Background Skeletal muscle is a large and clinically relevant body component that has been
difficult and impractical to quantify outside of specialized facilities. Advances in smartphone …

Background & aims Visual body composition (VBC) estimates produced from smartphone-
based artificial intelligence represent a user-friendly and convenient way to automate body …

Background Digital imaging analysis (DIA) estimates collected from mobile applications
comprise a novel technique that can collect body composition estimates remotely without the …

Digital anthropometry by three-dimensional optical imaging systems and smartphones has
recently been shown to provide non-invasive, precise, and accurate anthropometric and …

The creation of personalized anatomical digital twins is important in the fields of medicine
computer graphics sports science and biomechanics. To observe a subject's anatomy …

Familial partial lipodystrophy (FPLD) is a heterogenous group of syndromes associated with
a high prevalence of cardiometabolic diseases. Prior work has proposed DEXA-derived fat …

Inter-individual variation in fat distribution is increasingly recognized as clinically important
but is not routinely assessed in clinical practice, in part because medical imaging has not …