Shape Up! — Publications

Papers tagged shape-up — 3D optical body scanning and blood biomarkers across the lifecourse

53 publications · sorted by year, newest first.

2025

Deep Learning Enables Large-Scale Shape and Appearance Modeling in Total-Body DXA Imaging

Bunnell A, Cataldi D, Glaser Y, Wolfgruber T, Heymsfield SB, Zonderman AB, Kelly TL, Sadowski P, Shepherd J

Lecture notes in computer science, , 262-276 (2025)

DOI: 10.1007/978-3-032-06774-6_20

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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, 8, 79 (2025)

DOI: 10.1038/s41746-025-01469-6

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2024

Accurate Prediction of 3D Humanoid Avatars for Anthropometric Modeling

Heymsfield SB, McCarthy C, Wong M, Brown J, Bennett JP, Shepherd J

Current Developments in Nutrition, 8, 103558 (2024)

DOI: 10.1016/j.cdnut.2024.103558

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Author Correction: Trans-ancestral genome-wide association study of longitudinal pubertal height growth and shared heritability with adult health outcomes

Bradfeld JP, Kember RL, Ulrich A, Balkhiyarova Z, Alyass A, Aris IM, Bell JA, Broadaway KA, Chen Z, Chai JF, Davies NM, Fernández‐Orth D, Bustamante M, Fore R, Ganguli A, Heiskala A, Hottenga J, Íñiguez C, Kobes S, Leinonen JT, Lowry E, Lyytikäinen L, Mahajan A, Pitkänen N, Schnurr TM, Have CT, Strachan DP, Thiering E, Vogelezang S, Wade KH, Wang CA, Wong A, Holm LA, Chesi A, Choong CS, Cruz M, Elliott P, Franks S, Frithiof-Bøjsøe C, Gauderman WJ, Glessner J, Gilsanz V, Griesman K, Hanson RL, Kaakinen M, Kalkwarf HJ, Kelly A, Kindler JM, Kähönen M, Lança C, Lappe JM, Lee S, McCormack SE, Mentch F, Mitchell JA, Mononen N, Niinikoski H, Oken E, Pahkala K, Sim X, Teo Y, Baier LJ, Beijsterveldt TV, Adair LS, Boomsma DI, Geus EJCD, Guxens M, Eriksson JG, Felix JF, Gilliland FD, Biobank PM, Hansen T, Hardy R, Hivert M, Holm J, Jaddoe VWV, Järvelin M, Lehtimäki T, Mackey DA, Meyre D, Mohlke KL, Mykkänen J, Oberfeld S, Pennell CE, Perry JRB, Raitakari OT, Rivadeneira F, Saw S, Sebért S, Shepherd J, Standl M, Sørensen TIA, Timpson NJ, Torrent M, Willemsen G, Hyppönen E, Power C, McCarthy MI, Freathy RM, Widén E

Genome biology, 25, 129 (2024)

DOI: 10.1186/s13059-024-03276-w

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Prediction of Total and Regional Body Composition from 3D BodyShape

Cipolla R, Qiao C, Rolfe EDL, Brage S, Mak E, Sengupta A, Powell RC, Watson L, Heymsfield SB, Shepherd J, Wareham NJ

Research Square, , (2024)

DOI: 10.21203/rs.3.rs-4251510/v1

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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

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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, 48, 1741-1747 (2024)

DOI: 10.1038/s41366-024-01614-3

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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, 10, 72 (2024)

DOI: 10.1038/s41526-024-00412-5

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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, 43, 2430-2437 (2024)

DOI: 10.1016/j.clnu.2024.09.028

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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, 4, 13 (2024)

DOI: 10.1038/s43856-024-00434-w

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Clinical Anthropometrics and Body Composition from 3-Dimensional Optical Imaging

Minetto MA, Busso C, Ferraris A, Pietrobelli A, Shepherd J, McCarthy C, Heymsfield SB

Journal of Visualized Experiments, , (2024)

DOI: 10.3791/66698

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

Qiao C, Rolfe EDL, Mak E, Sengupta A, Powell RC, Watson L, Heymsfield SB, Shepherd J, Wareham NJ, Brage S, Cipolla R

npj Digital Medicine, 7, 298 (2024)

DOI: 10.1038/s41746-024-01289-0

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2023

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

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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, 34, 799-806 (2023)

DOI: 10.1016/j.numecd.2023.12.014

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Equations for smartphone prediction of adiposity and appendicular lean mass in youth soccer players

Minetto MA, Pietrobelli A, Ferraris A, Busso C, Magistrali M, Vignati C, Sieglinger BA, Bruner DM, Shepherd J, Heymsfield SB

Scientific Reports, 13, 20734 (2023)

DOI: 10.1038/s41598-023-48055-y

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Development and validation of a rapid multicompartment body composition model using 3-dimensional optical imaging and bioelectrical impedance analysis

Bennett JP, Cataldi D, Liu YE, Kelly NN, Quon BK, Schoeller DA, Kelly TL, Heymsfield SB, Shepherd J

Clinical Nutrition, 43, 346-356 (2023)

DOI: 10.1016/j.clnu.2023.12.009

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Advances in digital anthropometric body composition assessment: neural network algorithm prediction of appendicular lean mass

Marazzato F, McCarthy C, Field RH, Nguyen HTN, Nguyen T, Shepherd J, Tinsley GM, Heymsfield SB

European Journal of Clinical Nutrition, 78, 452-454 (2023)

DOI: 10.1038/s41430-023-01396-3

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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, 42, 1619-1630 (2023)

DOI: 10.1016/j.clnu.2023.07.012

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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, 118, 812-821 (2023)

DOI: 10.1016/j.ajcnut.2023.08.004

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Translating digital anthropometry measurements obtained from different 3D body image scanners

Ashby N, LaPorte GJ, Richardson D, Scioletti M, Heymsfield SB, Shepherd J, McGurk M, Bustillos B, Gist NH, Thomas DM

European Journal of Clinical Nutrition, 77, 872-880 (2023)

DOI: 10.1038/s41430-023-01289-5

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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, 118, 657-671 (2023)

DOI: 10.1016/j.ajcnut.2023.07.010

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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, Maskarinec G, Weiss EJ, Rood J, Varanoske AN, Pasiakos SM, Heymsfield SB, Shepherd J

American Journal of Clinical Nutrition, 117, 802-813 (2023)

DOI: 10.1016/j.ajcnut.2023.02.006

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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, 117, 794-801 (2023)

DOI: 10.1016/j.ajcnut.2023.02.003

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2022

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, 49, 6395-6409 (2022)

DOI: 10.1002/mp.15843

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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, 30, 1589-1598 (2022)

DOI: 10.1002/oby.23470

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Digital Anthropometry for Body Circumference Measurements: European Phenotypic Variations throughout the Decades

Minetto MA, Pietrobelli A, Busso C, Bennett JP, Ferraris A, Shepherd J, Heymsfield SB

Journal of Personalized Medicine, 12, 906 (2022)

DOI: 10.3390/jpm12060906

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Anthropometric evaluation of a 3D scanning mobile application

Smith B, McCarthy C, Dechenaud M, Wong MC, Shepherd J, Heymsfield SB

Obesity, 30, 1181-1188 (2022)

DOI: 10.1002/oby.23434

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2021

Evaluating the Accuracy of an Hallucinatory Algorithm to Predict Body Shape Changes from Dieting and Physical Activity

Shepherd J, Wong MC, Tian IY, Liu YE, Kennedy S, LOWE D, Kelly NN, Wong JM, Ebbeling CB, Ludwig DS, Weiss EJ, Curless B, Heymsfield SB

DOI: 10.15221/21.43

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Creating Accurate Representations of DXA Scans from 3D Optical Body Surface Scans for Arbitrary Regional Body Composition Analysis

Leong LT, Wong MC, Liu YE, Kelly NN, PIAZZA M, GARRY S, Heymsfield SB, Shepherd J

DOI: 10.15221/21.35

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3D Optical Body Composition Accuracy across Subgroups of BMI and Race/Ethnicity

Wong MC, LIU YE, Kennedy S, Kelly NN, Maskarinec G, Garber AK, Wong JM, Ebbeling CB, Ludwig DS, Weiss EJ, Pujades S, Heymsfield SB, Shepherd J

DOI: 10.15221/21.36

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Predicting Muscular Strength with 3D Optical in a Diverse Adult Population

Cataldi D, Bennett J, Quon BK, Liu YE, Kelly NN, Heymsfield SB, Shepherd J

DOI: 10.15221/21.38

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Total body and regional surface area: Quantification with low‐cost three‐dimensional optical imaging systems

Dechenaud M, Kennedy S, Sobhiyeh S, Shepherd J, Heymsfield SB

American Journal of Physical Anthropology, 175, 865-875 (2021)

DOI: 10.1002/ajpa.24243

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Digital anthropometric evaluation of young children: comparison to results acquired with conventional anthropometry

Kennedy S, Smith B, Sobhiyeh S, Dechenaud M, Wong MC, Kelly NN, Shepherd J, Heymsfield SB

European Journal of Clinical Nutrition, 76, 251-260 (2021)

DOI: 10.1038/s41430-021-00938-x

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Digital anthropometric volumes: Toward the development and validation of a universal software

Sobhiyeh S, Dunkel A, Dechenaud M, Mehrnezhad A, Kennedy S, Shepherd J, Wolenski PR, Heymsfield SB

Medical Physics, 48, 3654-3664 (2021)

DOI: 10.1002/mp.14829

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A pose‐independent method for accurate and precise body composition from 3D optical scans

Wong MC, Ng BK, Tian IY, Sobhiyeh S, Pagano I, Dechenaud M, Kennedy S, Liu YE, Kelly NN, Chow DC, Garber AK, Maskarinec G, Pujades S, Black MJ, Curless B, Heymsfield SB, Shepherd J

Obesity, 29, 1835-1847 (2021)

DOI: 10.1002/oby.23256

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Assessment of clinical measures of total and regional body composition from a commercial 3-dimensional optical body scanner

Bennett JP, Liu YE, Quon BK, Kelly NN, Wong MC, Kennedy S, Chow DC, Garber AK, Weiss EJ, Heymsfield SB, Shepherd J

Clinical Nutrition, 41, 211-218 (2021)

DOI: 10.1016/j.clnu.2021.11.031

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2020

Correction: Clinical anthropometrics and body composition from 3D whole-body surface scans

Ng BK, Hinton B, Fan B, Kanaya AM, Shepherd J

European Journal of Clinical Nutrition, 75, 574 (2020)

DOI: 10.1038/s41430-020-00808-y

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Fully Automated Pipeline for Body Composition Estimation from 3D Optical Scans using Principal Component Analysis: A Shape Up Study

Sobhiyeh S, Borel N, Dechenaud M, Graham CA, Wong MC, Wolenski PR, Shepherd J, Heymsfield SB

DOI: 10.1109/embc44109.2020.9175211

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Diet Quality and Visceral Adiposity among a Multiethnic Population of Young, Middle, and Older Aged Adults

Panizza C, Wong MC, Kelly NN, Liu YE, Shvetsov YB, Lowe DA, Weiss EJ, Heymsfield SB, Kennedy S, Boushey CJ, Maskarinec G, Shepherd J

Current Developments in Nutrition, 4, nzaa090 (2020)

DOI: 10.1093/cdn/nzaa090

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Digital anthropometry for body circumference measurements: Toward the development of universal three‐dimensional optical system analysis software

Sobhiyeh S, Kennedy S, Dunkel A, Dechenaud M, Weston J, Shepherd J, Wolenski PR, Heymsfield SB

Obesity Science & Practice, 7, 35-44 (2020)

DOI: 10.1002/osp4.467

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Predicting 3D body shape and body composition from conventional 2D photography

Tian IY, Ng BK, Wong MC, Kennedy S, Hwaung P, Kelly NN, Liu E, Garber AK, Curless B, Heymsfield SB, Shepherd J

Medical Physics, 47, 6232-6245 (2020)

DOI: 10.1002/mp.14492

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Novel body fat estimation using machine learning and 3-dimensional optical imaging

Harty PS, Sieglinger BA, Heymsfield SB, Shepherd J, Bruner DM, Stratton MT, Tinsley GM

European Journal of Clinical Nutrition, 74, 842-845 (2020)

DOI: 10.1038/s41430-020-0603-x

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2019

Crotch detection on 3D optical scans of human subjects

Sobhiyeh S, Dunkel A, Dechenaud M, Kennedy S, Shepherd J, Heymsfield SB, Wolenski PR

Electronic Imaging, 31, 10-1 (2019)

DOI: 10.2352/issn.2470-1173.2019.16.3dmp-010

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Hole Filling in 3D Scans for Digital Anthropometric Applications

Sobhiyeh S, Dechenaud M, Dunkel A, LaBorde ML, Kennedy S, Shepherd J, Heymsfield SB, Wolenski PR

DOI: 10.1109/embc.2019.8856713

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Optical imaging technology for body size and shape analysis: evaluation of a system designed for personal use

Kennedy S, Hwaung P, Kelly NN, Liu YE, Sobhiyeh S, Heo M, Shepherd J, Heymsfield SB

European Journal of Clinical Nutrition, 74, 920-929 (2019)

DOI: 10.1038/s41430-019-0501-2

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Children and Adolescents’ Anthropometrics Body Composition from 3‐D Optical Surface Scans

Wong MC, Ng BK, Kennedy S, Hwaung P, Liu EY, Kelly NN, Pagano I, Garber AK, Chow DC, Heymsfield SB, Shepherd J

Obesity, 27, 1738-1749 (2019)

DOI: 10.1002/oby.22637

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Detailed 3-dimensional body shape features predict body composition, blood metabolites, and functional strength: the Shape Up! studies

Ng BK, Sommer MJ, Wong MC, Pagano I, Nie Y, Fan B, Kennedy S, Bourgeois B, Kelly NN, Liu YE, Hwaung P, Garber AK, Chow DC, Vaisse C, Curless B, Heymsfield SB, Shepherd J

American Journal of Clinical Nutrition, 110, 1316-1326 (2019)

DOI: 10.1093/ajcn/nqz218

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