Michael C. Wong

Postdoctoral Researcher (T32, completed)

Publications (40)

• 3D convolutional deep learning for nonlinear estimation of body composition from whole body morphology
  Tian IY, Liu J, Wong MC, Kelly NN, Liu YE, Garber AK, Heymsfield SB, Curless B, Shepherd J
  npj Digital Medicine, 2025· doi:10.1038/s41746-025-01469-6
• 3D Convolutional Deep Learning for Nonlinear Estimation of Body Composition from Whole-Body Morphology
  Tian IY, Liu J, Wong MC, Kelly NN, Liu Y, Garber AK, Heymsfield SB, Curless B, Shepherd J
  Research Square, 2024· doi:10.21203/rs.3.rs-3935042/v1
• Accurate prediction of three-dimensional humanoid avatars for anthropometric modeling
  McCarthy C, Wong MC, Brown J, Ramirez S, Yang S, Bennett JP, Shepherd J, Heymsfield SB
  International Journal of Obesity, 2024· doi:10.1038/s41366-024-01614-3
• Evaluation of body shape as a human body composition assessment in isolated conditions and remote environments
  Wong MC, Bennett JP, Leong LT, Liu YE, Kelly NN, Cherry JA, Kloza K, Li B, Iuliano S, Sibonga JD, Sawyer A, Ayton J, Shepherd J
  npj Microgravity, 2024· doi:10.1038/s41526-024-00412-5
• Trunk-to-leg volume and appendicular lean mass from a commercial 3-dimensional optical body scanner for disease risk identification
  Bennett JP, Wong MC, Liu YE, Quon BK, Kelly NN, Garber AK, Heymsfield SB, Shepherd J
  Clinical Nutrition, 2024· doi:10.1016/j.clnu.2024.09.028
• Generative deep learning furthers the understanding of local distributions of fat and muscle on body shape and health using 3D surface scans
  Leong LT, Wong MC, Liu YE, Glaser Y, Quon BK, Kelly NN, Cataldi D, Sadowski P, Heymsfield SB, Shepherd J
  Communications Medicine, 2024· doi:10.1038/s43856-024-00434-w
• Medical imaging measurement of visceral adipose tissue thresholds associated with increased risk of cardiometabolic disease
  Bennett JP, Wong MC, Prado CM, Heymsfield SB, Shepherd J
  Journal of Clinical Densitometry, 2023· doi:10.1016/j.jocd.2023.101387
• Accuracy and Precision of Multiple Laboratory and Field Methods to The Criterion In Vivo Five-Compartment Body Composition Model and Their Association with Muscle Strength in Collegiate Athletes of Varying States of Hydration: The Da Kine Protocol Study
  Cataldi D, Bennett JP, Wong MC, Quon BK, Liu YE, Kelly NN, Kelly TL, Schoeller DA, Heymsfield SB, Shepherd J
  medRxiv, 2023· doi:10.1101/2023.05.30.23290630
• Deep Learning Furthers the Understanding of Local Distributions of Fat and Muscle on Body Shape and Health Using 3D Surface Scans
  Leong LT, Wong MC, Liu YE, Glaser Y, Quon BK, Kelly NN, Cataldi D, Sadowski P, Heymsfield SB, Shepherd J
  SSRN Electronic Journal, 2023· doi:10.2139/ssrn.4436398
• Reply to Y Lu et al.
  Bennett JP, Liu YE, Kelly NN, Quon BK, Wong MC, McCarthy C, Heymsfield SB, Shepherd J
  American Journal of Clinical Nutrition, 2023· doi:10.1016/j.ajcnut.2023.01.004
• Predictors of visceral and subcutaneous adipose tissue and muscle density: The ShapeUp! Kids study
  Maskarinec G, Shvetsov YB, Wong MC, Cataldi D, Bennett JP, Garber AK, Buchthal SD, Heymsfield SB, Shepherd J
  Nutrition Metabolism and Cardiovascular Diseases, 2023· doi:10.1016/j.numecd.2023.12.014
• Automated body composition estimation from device-agnostic 3D optical scans in pediatric populations
  Tian IY, Wong MC, Nguyen WM, Kennedy S, McCarthy C, Kelly NN, Liu YE, Garber AK, Heymsfield SB, Curless B, Shepherd J
  Clinical Nutrition, 2023· doi:10.1016/j.clnu.2023.07.012
• Cross-sectional assessment of body composition and detection of malnutrition risk in participants with low body mass index and eating disorders using 3D optical surface scans
  Garber AK, Bennett JP, Wong MC, Tian IY, Maskarinec G, Kennedy S, McCarthy C, Kelly NN, Liu YE, Machen VI, Heymsfield SB, Shepherd J
  American Journal of Clinical Nutrition, 2023· doi:10.1016/j.ajcnut.2023.08.004
• Accuracy and precision of multiple body composition methods and associations with muscle strength in athletes of varying hydration: The Da Kine Study
  Cataldi D, Bennett JP, Wong MC, Quon BK, Liu YE, Kelly NN, Kelly TL, Schoeller DA, Heymsfield SB, Shepherd J
  Clinical Nutrition, 2023· doi:10.1016/j.clnu.2023.11.040
• Accuracy and Precision of 3-dimensional Optical Imaging for Body Composition by Age, BMI, and Ethnicity
  Wong MC, Bennett JP, Quon BK, Leong LT, Tian IY, Liu YE, Kelly NN, McCarthy C, Chow DC, Pujades S, Garber AK, Maskarinec G, Heymsfield SB, Shepherd J
  American Journal of Clinical Nutrition, 2023· doi:10.1016/j.ajcnut.2023.07.010
• Monitoring body composition change for intervention studies with advancing 3D optical imaging technology in comparison to dual-energy X-ray absorptiometry
  Wong MC, Bennett JP, Leong LT, Tian IY, Liu YE, Kelly NN, McCarthy C, Wong JM, Ebbeling CB, Ludwig DS, Irving BA, Scott MC, Stampley J, Davis B, Johannsen NM, Matthews R, Vincellette C, Garber AK, ...
  American Journal of Clinical Nutrition, 2023· doi:10.1016/j.ajcnut.2023.02.006
• Smartphone prediction of skeletal muscle mass: model development and validation in adults
  McCarthy C, Tinsley GM, Yang S, Irving BA, Wong MC, Bennett JP, Shepherd J, Heymsfield SB
  American Journal of Clinical Nutrition, 2023· doi:10.1016/j.ajcnut.2023.02.003
• Accuracy and Precision of 3D Optical Imaging for Body Composition and their Associations to Metabolic Markers by Age, BMI, and Ethnicity
  Wong MC, Bennett JP, Quon BK, Leong LT, Tian IY, Liu YE, Kelly NN, McCarthy C, Chow DC, Pujades S, Garber AK, Maskarinec G, Heymsfield SB, Shepherd J
  medRxiv, 2022· doi:10.1101/2022.11.02.22281819
• Emergence of the adolescent obesity epidemic in the United States: five-decade visualization with humanoid avatars
  Bennett JP, Wong MC, McCarthy C, Fearnbach N, Queen K, Shepherd J, Heymsfield SB
  International Journal of Obesity, 2022· doi:10.1038/s41366-022-01153-9
• What Is a 2021 Reference Body?
  Müller MJ, Bosy‐Westphal A, Braun W, Wong MC, Shepherd J, Heymsfield SB
  Nutrients, 2022· doi:10.3390/nu14071526
• Emergence of the obesity epidemic: 6-decade visualization with humanoid avatars
  Wong MC, McCarthy C, Fearnbach N, Yang S, Shepherd J, Heymsfield SB
  American Journal of Clinical Nutrition, 2022· doi:10.1093/ajcn/nqac005
• A device‐agnostic shape model for automated body composition estimates from 3D optical scans
  Tian IY, Wong MC, Kennedy S, Kelly NN, Liu YE, Garber AK, Heymsfield SB, Curless B, Shepherd J
  Medical Physics, 2022· doi:10.1002/mp.15843
• Three‐dimensional optical body shape and features improve prediction of metabolic disease risk in a diverse sample of adults
  Bennett JP, Liu YE, Quon BK, Kelly NN, Leong LT, Wong MC, Kennedy S, Chow DC, Garber AK, Weiss EJ, Heymsfield SB, Shepherd J
  Obesity, 2022· doi:10.1002/oby.23470
• Subcutaneous and visceral fat assessment by DXA and MRI in older adults and children
  Maskarinec G, Shvetsov YB, Wong MC, Garber AK, Monroe KR, Ernst T, Buchthal SD, Lim U, Marchand LL, Heymsfield SB, Shepherd J
  Obesity, 2022· doi:10.1002/oby.23381
• Next-generation smart watches to estimate whole-body composition using bioimpedance analysis: accuracy and precision in a diverse, multiethnic sample
  Bennett JP, Liu YE, Kelly NN, Quon BK, Wong MC, McCarthy C, Heymsfield SB, Shepherd J
  American Journal of Clinical Nutrition, 2022· doi:10.1093/ajcn/nqac200

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