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

Imaging Informatics (200) Tools, Programs and Algorithms (275)

Published on in Vol 4, No 1 (2016): Jan-Mar

Computerized Automated Quantification of Subcutaneous and Visceral Adipose Tissue From Computed Tomography Scans: Development and Validation Study

Computerized Automated Quantification of Subcutaneous and Visceral Adipose Tissue From Computed Tomography Scans: Development and Validation Study

Computerized Automated Quantification of Subcutaneous and Visceral Adipose Tissue From Computed Tomography Scans: Development and Validation Study

Authors of this article:

Young Jae Kim1, 2 Author Orcid Image ;   Ji Won Park3, 4, 5 Author Orcid Image ;   Jong Wan Kim6 Author Orcid Image ;   Chan-Soo Park1 Author Orcid Image ;   John Paul S Gonzalez7 Author Orcid Image ;   Seung Hyun Lee2 Author Orcid Image ;   Kwang Gi Kim1 Author Orcid Image ;   Jae Hwan Oh8 Author Orcid Image
Article Authors Cited by (25) Tweetations (3) Metrics

Journals

  1. Lee J, Park J, Heo J, Ahn H, Jang W, Ham W, Rha K, Choi Y. Muscle Characteristics Obtained Using Computed Tomography as Prognosticators in Patients with Castration-Resistant Prostate Cancer. Cancers 2020;12(7):1864 View
  2. Lee S, Liu J, Yao J, Kanarek A, Summers R, Pickhardt P. Fully automated segmentation and quantification of visceral and subcutaneous fat at abdominal CT: application to a longitudinal adult screening cohort. The British Journal of Radiology 2018:20170968 View
  3. Zarinabad N, Meeus E, Manias K, Foster K, Peet A. Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis. JMIR Medical Informatics 2018;6(2):e30 View
  4. Tanaka M, Okada H, Hashimoto Y, Kumagai M, Nishimura H, Fukui M. Low-attenuation muscle is a predictor of diabetes mellitus: A population-based cohort study. Nutrition 2020;74:110752 View
  5. Liu T, Udupa J, Miao Q, Tong Y, Torigian D. Quantification of body‐torso‐wide tissue composition on low‐dose CT images via automatic anatomy recognition. Medical Physics 2019;46(3):1272 View
  6. Liu T, Pan J, Torigian D, Xu P, Miao Q, Tong Y, Udupa J. ABCNet: A new efficient 3D dense‐structure network for segmentation and analysis of body tissue composition on body‐torso‐wide CT images. Medical Physics 2020;47(7):2986 View
  7. Cespedes Feliciano E, Chen W, Bradshaw P, Prado C, Alexeeff S, Albers K, Castillo A, Caan B. Adipose Tissue Distribution and Cardiovascular Disease Risk Among Breast Cancer Survivors. Journal of Clinical Oncology 2019;37(28):2528 View
  8. Shen N, Li X, Zheng S, Zhang L, Fu Y, Liu X, Li M, Li J, Guo S, Zhang H. Automated and accurate quantification of subcutaneous and visceral adipose tissue from magnetic resonance imaging based on machine learning. Magnetic Resonance Imaging 2019;64:28 View
  9. Voglino C, Tirone A, Ciuoli C, Benenati N, Paolini B, Croce F, Gaggelli I, Vuolo M, Cuomo R, Grimaldi L, Vuolo G. Cardiovascular Benefits and Lipid Profile Changes 5 Years After Bariatric Surgery: A Comparative Study Between Sleeve Gastrectomy and Roux-en-Y Gastric Bypass. Journal of Gastrointestinal Surgery 2020;24(12):2722 View
  10. Tanaka M, Okada H, Hashimoto Y, Kumagai M, Nishimura H, Oda Y, Fukui M. Relationship between metabolic syndrome and trunk muscle quality as well as quantity evaluated by computed tomography. Clinical Nutrition 2020;39(6):1818 View
  11. Srikumar T, Siegel E, Gu Y, Balagurunathan Y, Garcia A, Chen Y, Zhou J, Zhao X, Gillies R, Clark W, Gamenthaler A, Choi J, Shibata D. Semiautomated Measure of Abdominal Adiposity Using Computed Tomography Scan Analysis. Journal of Surgical Research 2019;237:12 View
  12. Tanaka M, Okada H, Hashimoto Y, Kumagai M, Nishimura H, Fukui M. Trunk muscle quality and quantity predict the development of metabolic syndrome and the increase in the number of its components in individuals without metabolic syndrome. Nutrition, Metabolism and Cardiovascular Diseases 2020;30(7):1161 View
  13. Hussein S, Bagci U, Green A, Watane A, Reiter D, Chen X, Papadakis G, Wood B, Cypess A, Osman M. Automatic Segmentation and Quantification of White and Brown Adipose Tissues from PET/CT Scans. IEEE Transactions on Medical Imaging 2017;36(3):734 View
  14. Tanaka M, Okada H, Hashimoto Y, Kumagai M, Nishimura H, Oda Y, Fukui M. Relationship between nonalcoholic fatty liver disease and muscle quality as well as quantity evaluated by computed tomography. Liver International 2020;40(1):120 View
  15. Schaudinn A, Hudak A, Linder N, Reinhardt M, Stocker G, Lordick F, Denecke T, Busse H. Toward a Routine Assessment of Visceral Adipose Tissue Volume from Computed Tomographic Data. Obesity 2021;29(2):294 View
  16. Han J, Tang M, Zhang G, Lu C, She J, Wu G. The Effect and Mechanism of Subcutaneous and Visceral Adipose Tissue Loss on Gastric Cancer Patients With Cachexia. SSRN Electronic Journal 2020 View
  17. Matondang S, Adiandrian B, Karismaputri K, Marcella C, Prihartono J, Tahapary D, Yamada Y. Simple anthropometric measures to predict visceral adipose tissue area in middle-aged Indonesian men. PLOS ONE 2023;18(1):e0280033 View
  18. Han J, Tang M, Lu C, Shen L, She J, Wu G. Subcutaneous, but not visceral, adipose tissue as a marker for prognosis in gastric cancer patients with cachexia. Clinical Nutrition 2021;40(9):5156 View
  19. Fontanella C, Toniolo I, Foletto M, Prevedello L, Carniel E. Mechanical Behavior of Subcutaneous and Visceral Abdominal Adipose Tissue in Patients with Obesity. Processes 2022;10(9):1798 View
  20. Boccara E, Golan S, Beeri M. The association between regional adiposity, cognitive function, and dementia-related brain changes: a systematic review. Frontiers in Medicine 2023;10 View

Books/Policy Documents

  1. Bridge C, Rosenthal M, Wright B, Kotecha G, Fintelmann F, Troschel F, Miskin N, Desai K, Wrobel W, Babic A, Khalaf N, Brais L, Welch M, Zellers C, Tenenholtz N, Michalski M, Wolpin B, Andriole K. OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis. View
  2. de Carvalho Felinto J, Poloni K, de Lima Freire P, Aily J, de Almeida A, Pedroso M, Mattiello S, Ferrari R. Computational Science and Its Applications – ICCSA 2018. View
  3. Devi B, Misbha D. Computer Networks, Big Data and IoT. View