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Body Fat Assessment Method Using CT Images with Separation Mask Algorithm

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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.

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Acknowledgment

This research was supported by the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean government (MEST) (2011–0019794) and National Cancer Center No. NCC-1110160.

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Authors and Affiliations

  1. Biomedical Engineering Branch, Division of Convergence Technology, National Cancer Center, 323 Ilsan-ro, Ilsandong-gu, Goyang-si, Gyeonggi-do, 410-769, South Korea

    Young Jae Kim, Tae Yun Kim & Kwang Gi Kim

  2. Department of Radiology, Seoul national University Hospital, Seoul, South Korea

    Seung Hong Choi

  3. Department of Plasma Display, Kwangwoon University, Seoul, South Korea

    Young Jae Kim & Seung Hyun Lee

  4. Department of Clinical Nursing, College of Medicine, University of Ulsan, Seoul, South Korea

    Jeong Yun Park

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  1. Young Jae Kim
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  2. Seung Hyun Lee
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  3. Tae Yun Kim
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  4. Jeong Yun Park
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  5. Seung Hong Choi
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  6. Kwang Gi Kim
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Correspondence to Kwang Gi Kim.

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Kim, Y.J., Lee, S.H., Kim, T.Y. et al. Body Fat Assessment Method Using CT Images with Separation Mask Algorithm. J Digit Imaging 26, 155–162 (2013). https://doi.org/10.1007/s10278-012-9488-0

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  • DOI: https://doi.org/10.1007/s10278-012-9488-0

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