Development of an automated 3D segmentation program for volume quantification of body fat distribution using CT.
Development of an automated 3D segmentation program for volume quantification of body fat distribution using CT.
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DOI：
10.6009/jjrt.64.1177
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发表时间：
2008-09
期刊：
影响因子：
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通讯作者：
S. Ohshima;Shuji Yamamoto;T. Yamaji;Masahiro Suzuki;M. Mutoh;M. Iwasaki;S. Sasazuki;Ken Kotera;S. Tsugane;Y. Muramatsu;N. Moriyama
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文献类型：
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作者：
S. Ohshima;Shuji Yamamoto;T. Yamaji;Masahiro Suzuki;M. Mutoh;M. Iwasaki;S. Sasazuki;Ken Kotera;S. Tsugane;Y. Muramatsu;N. Moriyama
本研究的目的是开发一种计算工具，用于全自动分割体脂肪分布的体积CT图像。我们开发了一种算法来自动识别身体周长和将内脏脂肪与皮下脂肪分开的内部轮廓。横膈膜表面可以通过基于模型的分割来提取，以匹配CT图像中的肺的底表面，用于确定腹部的上限。腹型肥胖或肥胖相关代谢综合征的定量评价功能由原型三维（3D）图像处理工作站实现。可以计算每个受试者的内脏脂肪与总脂肪和内脏脂肪与皮下脂肪的体积比。此外，皮下区域和内脏脂肪层的颜色强度映射在理解3D表面显示的腹部肥胖风险方面是相当明显的。所获得的初步结果在医疗检查中非常有用，并且有助于通过3D可视化和分析来提高在整个腹部范围内检查肥胖的效率。
The objective of this study was to develop a computing tool for full-automatic segmentation of body fat distributions on volumetric CT images. We developed an algorithm to automatically identify the body perimeter and the inner contour that separates visceral fat from subcutaneous fat. Diaphragmatic surfaces can be extracted by model-based segmentation to match the bottom surface of the lung in CT images for determination of the upper limitation of the abdomen. The functions for quantitative evaluation of abdominal obesity or obesity-related metabolic syndrome were implemented with a prototype three-dimensional (3D) image processing workstation. The volumetric ratios of visceral fat to total fat and visceral fat to subcutaneous fat for each subject can be calculated. Additionally, color intensity mapping of subcutaneous areas and the visceral fat layer is quite obvious in understanding the risk of abdominal obesity with the 3D surface display. Preliminary results obtained have been useful in medical checkups and have contributed to improved efficiency in checking obesity throughout the whole range of the abdomen with 3D visualization and analysis.