Computed Tomography Image Analysis of Body Fat Based on Multi-Image Information

Abstract

Body fat assessment is required as part of an objective health assessment, both for nonobese and obese people. Image-based body fat assessment will enable faster diagnosis. Body fat analysis that accounts for age and sex will help in both diagnosis and correlating diseases and fat distribution. After evaluating computed tomography imaging algorithms to identify and segment human abdominal and subcutaneous fat, we present an improved region growing scale-invariant feature transform algorithm. It applies Naive Bayes image thresholding for key point selection and image matching. This method enables rapid and accurate comparison and matching of images from multiple databases and improves the efficiency of image processing.

Visceral fat and attribute-based medicine in chronic kidney disease

“…Imaging measurement of adiposity can be performed by various methods, including computed tomography (CT), magnetic resonance imaging (MRI), dual-energy X-ray absorptiometry, and electrical bioimpedance ( 93 ). Among these, only CT accurately measures visceral fat area (VFA) ( 94 ). CT can be performed rapidly and interpreted to segment adipose tissue deposits and measure their area or volume ( 80 ).…”

“…CT can be performed rapidly and interpreted to segment adipose tissue deposits and measure their area or volume ( 80 ). CT produces high-resolution images conveniently and with high repeatability ( 94 ), providing accurate localization data ( 95 ). Although CT is expensive and exposes the patient to radiation, quantitative CT is currently the technology of choice for the measurement and analysis of VFA ( 96 ).…”