This paper is in the following e-collection/theme issue:

mHealth for Data Collection and Research (981) Innovations and Technology for Healthy Eating Education (425) Instruments and Questionnaires for Nutrition and Food Intake (169) mHealth for Wellness, Behavior Change and Prevention (2922)

Published on in Vol 8, No 3 (2020): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15294, first published .
Volumetric Food Quantification Using Computer Vision on a Depth-Sensing Smartphone: Preclinical Study

Volumetric Food Quantification Using Computer Vision on a Depth-Sensing Smartphone: Preclinical Study

Volumetric Food Quantification Using Computer Vision on a Depth-Sensing Smartphone: Preclinical Study

Authors of this article:

David Herzig1 Author Orcid Image ;   Christos T Nakas2, 3 Author Orcid Image ;   Janine Stalder1 Author Orcid Image ;   Christophe Kosinski1 Author Orcid Image ;   Céline Laesser1 Author Orcid Image ;   Joachim Dehais1 Author Orcid Image ;   Raphael Jaeggi1 Author Orcid Image ;   Alexander Benedikt Leichtle3 Author Orcid Image ;   Fried-Michael Dahlweid4 Author Orcid Image ;   Christoph Stettler1 Author Orcid Image ;   Lia Bally1 Author Orcid Image
Article Authors Cited by (21) Tweetations (7) Metrics

Journals

  1. Steenkamp D, Eby E, Gulati N, Liao B. Adherence and Persistence to Insulin Therapy in People with Diabetes: Impact of Connected Insulin Pen Delivery Ecosystem. Journal of Diabetes Science and Technology 2022;16(4):995 View
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  4. Jia W, Ren Y, Li B, Beatrice B, Que J, Cao S, Wu Z, Mao Z, Lo B, Anderson A, Frost G, McCrory M, Sazonov E, Steiner-Asiedu M, Baranowski T, Burke L, Sun M. A Novel Approach to Dining Bowl Reconstruction for Image-Based Food Volume Estimation. Sensors 2022;22(4):1493 View
  5. Barmanray R, Kyi M, Fourlanos S. Assistive technology for diabetes management: a toolkit. British Journal of Healthcare Management 2022;28(5):118 View
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  7. Vasiloglou M, Marcano I, Lizama S, Papathanail I, Spanakis E, Mougiakakou S. Multimedia Data-Based Mobile Applications for Dietary Assessment. Journal of Diabetes Science and Technology 2023;17(4):1056 View
  8. Moshfegh A, Rhodes D, Martin C. National Food Intake Assessment: Technologies to Advance Traditional Methods. Annual Review of Nutrition 2022;42(1):401 View
  9. Karabay A, Bolatov A, Varol H, Chan M. A Central Asian Food Dataset for Personalized Dietary Interventions. Nutrients 2023;15(7):1728 View
  10. Zhang S, Callaghan V, Che Y. Image-based methods for dietary assessment: a survey. Journal of Food Measurement and Characterization 2024;18(1):727 View
  11. Serra M, Alceste D, Hauser F, Hulshof P, Meijer H, Thalheimer A, Steinert R, Gerber P, Spector A, Gero D, Bueter M. Assessing daily energy intake in adult women: validity of a food-recognition mobile application compared to doubly labelled water. Frontiers in Nutrition 2023;10 View
  12. Shonkoff E, Cara K, Pei X, Chung M, Kamath S, Panetta K, Hennessy E. AI-based digital image dietary assessment methods compared to humans and ground truth: a systematic review. Annals of Medicine 2023;55(2) View
  13. Zhang R, Ouyang D, He L, Kuang L, Bai H. Recognize after early fusion: the Chinese food recognition based on the alignment of image and ingredients. Multimedia Systems 2024;30(2) View
  14. Baumgartner M, Kuhn C, Nakas C, Herzig D, Bally L. Carbohydrate Estimation Accuracy of Two Commercially Available Smartphone Applications vs Estimation by Individuals With Type 1 Diabetes: A Comparative Study. Journal of Diabetes Science and Technology 2024 View
  15. Chotwanvirat P, Prachansuwan A, Sridonpai P, Kriengsinyos W. Advancements in Using AI for Dietary Assessment Based on Food Images: Scoping Review. Journal of Medical Internet Research 2024;26:e51432 View
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Books/Policy Documents

  1. Nagarajan B, Khatun R, Bolaños M, Aguilar E, Angelini L, El Kamali M, Mugellini E, Khaled O, Boqué N, Tarro L, Radeva P. Digital Health Technology for Better Aging. View
  2. Chummun P, Suddul G, Armoogum S. Proceedings of World Conference on Information Systems for Business Management. View
  3. Abdur Rahman L, Papathanail I, Brigato L, Spanakis E, Mougiakakou S. Diabetes Digital Health, Telehealth, and Artificial Intelligence. View