Body Composition Analysis of Computed Tomography Scans in Clinical Populations: The Role of Deep Learning.
Journal:
Lifestyle genomics
Published Date:
Jan 1, 2020
Abstract
BACKGROUND: Body composition is increasingly being recognized as an important prognostic factor for health outcomes across cancer, liver cirrhosis, and critically ill patients. Computed tomography (CT) scans, when taken as part of routine care, provide an excellent opportunity to precisely measure the quantity and quality of skeletal muscle and adipose tissue. However, manual analysis of CT scans is costly and time-intensive, limiting the widespread adoption of CT-based measurements of body composition.
Authors
Keywords
Adipose Tissue
Body Composition
Body Mass Index
Cost-Benefit Analysis
Deep Learning
Humans
Image Processing, Computer-Assisted
Lumbar Vertebrae
Lumbosacral Region
Muscle, Skeletal
Neural Networks, Computer
Pattern Recognition, Automated
Reproducibility of Results
Subcutaneous Fat
Tomography, X-Ray Computed