MedShapeNet – a large-scale dataset of 3D medical shapes for computer vision

J Li, Z Zhou, J Yang, A Pepe, C Gsaxner… - Biomedical …, 2024 - degruyter.com
Objectives The shape is commonly used to describe the objects. State-of-the-art algorithms
in medical imaging are predominantly diverging from computer vision, where voxel grids …

Relationship of fat mass ratio, a biomarker for lipodystrophy, with cardiometabolic traits

S Agrawal, J Luan, BB Cummings, EJ Weiss… - Diabetes, 2024 - diabetesjournals.org
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 …

Updates on Methods for Body Composition Analysis: Implications for Clinical Practice

DM Thomas, I Crofford, J Scudder, B Oletti, A Deb… - Current Obesity …, 2025 - Springer
Background Recent technological advances have introduced novel methods for measuring
body composition, each with unique benefits and limitations. The choice of method often …

Prediction of total and regional body composition from 3D body shape

C Qiao, EDL Rolfe, E Mak, A Sengupta, R Powell… - NPJ Digital …, 2024 - nature.com
Accurate assessment of body composition is essential for evaluating the risk of chronic
disease. 3D body shape, obtainable using smartphones, correlates strongly with body …

HIT: Estimating Internal Human Implicit Tissues from the Body Surface

M Keller, V Arora, A Dakri… - Proceedings of the …, 2024 - openaccess.thecvf.com
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 …

Sex-based approach to estimate human body fat percentage from 2D camera images with deep learning and machine learning

SSA Alves, EF Ohata, PCS Junior, CB Barroso… - Measurement, 2023 - Elsevier
Obesity is one of the most concerning nutritional issues since it is a significant risk factor for
chronic diseases, including cardiovascular disease and diabetes. Many dietary disorders …

Machine learning allows robust classification of visceral fat in women with obesity using common laboratory metrics

F Palmieri, NF Akhtar, A Pané, A Jiménez… - Scientific Reports, 2024 - nature.com
The excessive accumulation and malfunctioning of visceral adipose tissue (VAT) is a major
determinant of increased risk of obesity-related comorbidities. Thus, risk stratification of …

An artificial intelligence–based pipeline for automated detection and localisation of epileptic sources from magnetoencephalography

L Zheng, P Liao, X Wu, M Cao, W Cui… - Journal of Neural …, 2023 - iopscience.iop.org
Objective. Magnetoencephalography (MEG) is a powerful non-invasive diagnostic modality
for presurgical epilepsy evaluation. However, the clinical utility of MEG map** for …

Sex‐specific causality of MRI‐derived body compositions on glycaemic traits: Mendelian randomization and observational study

Y Zhu, Q Wang, H Dai, T Hou, T Wang… - Diabetes, Obesity …, 2024 - Wiley Online Library
Aim To investigate the sex‐specific causality of body compositions in type 2 diabetes and
related glycaemic traits using Mendelian randomization (MR). Materials and Methods We …

[HTML][HTML] Body fat distribution: a crucial target for intervention in nonalcoholic fatty liver disease and fibrosis

K Wijarnpreecha, A Ahmed, D Kim - Hepatobiliary Surgery and …, 2022 - ncbi.nlm.nih.gov
© HepatoBiliary Surgery and Nutrition. All rights reserved. HepatoBiliary Surg Nutr 2022; 11
(5): 738-742| https://dx. doi. org/10.21037/hbsn-22-366 manner [hazard ratio (HR)= 2.23; …