Related references
Note: Only part of the references are listed.Population-Scale CT-based Body Composition Analysis of a Large Outpatient Population Using Deep Learning to Derive Age-, Sex-, and Race-specific Reference Curves
Kirti Magudia et al.
RADIOLOGY (2021)
Computed Tomography-based Body Composition Analysis and Its Role in Lung Cancer Care
Amelie S. Troschel et al.
JOURNAL OF THORACIC IMAGING (2020)
Deep learning for automated segmentation of pelvic muscles, fat, and bone from CT studies for body composition assessment
Robert Hemke et al.
SKELETAL RADIOLOGY (2020)
Volumetric evaluation of renal sinus adipose tissue on computed tomography images in bilateral nephrolithiasis patients
Lin Peng et al.
INTERNATIONAL UROLOGY AND NEPHROLOGY (2020)
Body Composition Analysis of Computed Tomography Scans in Clinical Populations: The Role of Deep Learning
Michael T. Paris
LIFESTYLE GENOMICS (2020)
Evaluation of automated computed tomography segmentation to assess body composition and mortality associations in cancer patients
Elizabeth M. Cespedes Feliciano et al.
JOURNAL OF CACHEXIA SARCOPENIA AND MUSCLE (2020)
Deep learning method for localization and segmentation of abdominal CT
Setareh Dabiri et al.
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2020)
Quantification of body composition in renal cell carcinoma patients: Comparing computed tomography and magnetic resonance imaging measurements
Michelle Higgins et al.
EUROPEAN JOURNAL OF RADIOLOGY (2020)
Validation study of a new semi-automated software program for CT body composition analysis
Naoki Takahashi et al.
ABDOMINAL RADIOLOGY (2017)
Decreased Skeletal Muscle Mass is Associated with an Increased Risk of Mortality after Radical Nephrectomy for Localized Renal Cell Cancer
Sarah P. Psutka et al.
JOURNAL OF UROLOGY (2016)
Cancer Cachexia in the Age of Obesity: Skeletal Muscle Depletion Is a Powerful Prognostic Factor, Independent of Body Mass Index
Lisa Martin et al.
JOURNAL OF CLINICAL ONCOLOGY (2013)
Definition and classification of cancer cachexia: an international consensus
Kenneth Fearon et al.
LANCET ONCOLOGY (2011)
A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care
Marina Mourtzakis et al.
APPLIED PHYSIOLOGY NUTRITION AND METABOLISM (2008)
Total body skeletal muscle and adipose tissue volumes: estimation from a single abdominal cross-sectional image
W Shen et al.
JOURNAL OF APPLIED PHYSIOLOGY (2004)