3D Shape-Based Body Composition Inference Model Using a Bayesian Network

Volume: 24, Issue: 1, Pages: 205 - 213
Published: Jan 1, 2020
Abstract
Body composition can be assessed in many different ways. High-end medical equipment, such as Dual-energy X-ray Absorptiometry (DXA), Computed Tomography (CT), and Magnetic Resonance Imaging (MRI) offers high-fidelity pixel/voxel-level assessment, but is prohibitive in cost. In the case of DXA and CT, the approach exposes users to ionizing radiation. Whole-body air displacement plethysmography (BOD POD) can accurately estimate body density, but...
Paper Details
Title
3D Shape-Based Body Composition Inference Model Using a Bayesian Network
Published Date
Jan 1, 2020
Volume
24
Issue
1
Pages
205 - 213
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