Title
Body Fat Assessment Method Using CT Images with Separation Mask Algorithm.
Abstract
In recent years, the number of obese population in Korea has been growing up along with the economic development, environmental factors, and the change in life style. Considering the growth of obese population and the adverse effect of obesity on health, it is getting more important to prevent and diagnose the obesity with the quantitative measurement of body fat that has become an important indicator for obesity. In this study, we proposed a procedure for the automated fat assessment from computed tomography (CT) data using image processing technique. The proposed method was applied to a single-CT image as well as CT-volume data, and results were correlated to those of dual-energy X-ray absorptiometry (DEXA) that is known as the reliable method for evaluating body fat. Using single-CT images, correlation coefficients between DEXA and the automated assessment and DEXA and the manual assessment were 0.038 and 0.058, respectively (P > 0.05). Hence, there was no significant correlation between three methods using the proposed method with single-CT images. On the other hand, in case of CT-volume data, the above correlation coefficients were increased to 0.826, 0.812, and 0.805, respectively (P < 0.01). Thus, DEXA and the proposed methods with CT-volume data showed highly significant correlation with each other. The results suggest that the proposed automated assessment using CT-volume data is a reliable method for the evaluation of body fat. It is expected that the clinical application of the proposed procedure will be helpful to reduce the time for the quantitative evaluation of patient's body fat.
Year
DOI
Venue
2013
10.1007/s10278-012-9488-0
J. Digital Imaging
Keywords
Field
DocType
Body fat,Fat assessment,Computed tomography (CT),DEXA,Separation mask
Nuclear medicine,Population,Body mass index,Life style,Image processing,Correlation,Obesity,Computed tomography,Radiology,Medicine
Journal
Volume
Issue
ISSN
26
2
1618-727X
Citations 
PageRank 
References 
2
0.39
2
Authors
6
Name
Order
Citations
PageRank
Young Jae Kim1284.62
Seung-Hyun Lee23310.22
Tae Yun Kim371.84
Jeong Yun Park420.39
Seung Hong Choi521.06
Kwang Gi Kim6186.10