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首页> 外文期刊>Journal of Digital Imaging >Body Fat Assessment Method Using CT Images with Separation Mask Algorithm
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Body Fat Assessment Method Using CT Images with Separation Mask Algorithm

机译：利用CT图像结合分离蒙版算法的人体脂肪评估方法

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摘要

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.
机译：近年来，随着经济发展，环境因素和生活方式的改变，韩国的肥胖人口数量一直在增长。考虑到肥胖人口的增长以及肥胖对健康的不利影响，通过定量测量已经成为肥胖的重要指标的肥胖来预防和诊断肥胖变得越来越重要。在这项研究中，我们提出了一种使用图像处理技术从计算机断层扫描（CT）数据自动评估脂肪的程序。所提出的方法已应用于单CT图像以及CT体数据，结果与双能量X射线吸收法（DEXA）的结果相关，该方法被称为评估人体脂肪的可靠方法。使用单CT图像，DEXA与自动评估之间的相关系数与DEXA与手动评估之间的相关系数分别为0.038和0.058（P> 0.05）。因此，使用所提出的方法与单CT图像的三种方法之间没有显着相关性。另一方面，在CT量数据的情况下，上述相关系数分别增加到0.826、0.812和0.805（P <0.01）。因此，DEXA和所提出的具有CT量数据的方法之间显示出高度显着的相关性。结果表明，建议的使用CT量数据进行自动评估是评估体脂的可靠方法。预期该建议程序的临床应用将有助于减少对患者体内脂肪进行定量评估的时间。

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  • 来源
    《Journal of Digital Imaging》 |2013年第2期|155-162|共8页
  • 作者

    Young Jae Kim; Seung Hyun Lee; Tae Yun Kim; Jeong Yun Park; Seung Hong Choi; Kwang Gi Kim;

  • 作者单位

    Biomedical Engineering Branch Division of Convergence Technology National Cancer Center">(1);

    Department of Plasma Display Kwangwoon University">(3);

    Department of Plasma Display Kwangwoon University">(3);

    Biomedical Engineering Branch Division of Convergence Technology National Cancer Center">(1);

    Department of Clinical Nursing College of Medicine University of Ulsan">(4);

    Department of Radiology Seoul national University Hospital">(2);

    Biomedical Engineering Branch Division of Convergence Technology National Cancer Center">(1);

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Body fat; Fat assessment; Computed tomography (CT); DEXA; Separation mask;

    机译：体内脂肪;脂肪评估;计算机断层扫描（CT）;DEXA;分离面罩;

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