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首页> 外文期刊>Ultrasonics, Ferroelectrics and Frequency Control, IEEE Transactions on >Automatic Measurement of Human Subcutaneous Fat with Ultrasound
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Automatic Measurement of Human Subcutaneous Fat with Ultrasound

机译：超声波自动测量人体皮下脂肪

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摘要

This paper presents an approach to measure human subcutaneous fat thickness automatically using ultrasound radio frequency (RF) signals. We propose using spatially compounded spectrum properties extracted from the RF signals of ultrasound for the purpose of fat boundary detection. Our fat detection framework consists of 4 main steps. The first step is to capture RF data from 11 ultrasound beam angles and at 4 different focal positions. Second, spectrum dispersion is calculated from the local spectrum of RF data using the shorttime Fourier transform and moment analysis. The values of the spectrum dispersion are encoded as gray-scale parametric images. Third, averaging is used to reduce speckle noise in the parametric image and improve the visualization of the subcutaneous fat layer. Finally, we apply Rosiniquests thresholding and random sample consensus boundary detection to extract the fat boundary. Our method was applied on 36 samples obtained in vivo at the suprailiac, thigh, and triceps of 9 human participants. In our study, high correlations between the manual and automatic ultrasound measurements (r > 0.7 at all body sites), and between the skinfold caliper and automatic ultrasound measurements (r > 0.7 at all body sites) were observed.
机译：本文提出了一种使用超声射频（RF）信号自动测量人体皮下脂肪厚度的方法。我们建议使用从超声的射频信号中提取的空间复合频谱特性来进行脂肪边界检测。我们的脂肪检测框架包括4个主要步骤。第一步是从11个超声波束角度并在4个不同的焦点位置捕获RF数据。其次，使用短时傅立叶变换和矩分析从RF数据的本地频谱计算频谱色散。频谱色散的值被编码为灰度参数图像。第三，平均可以减少参数图像中的斑点噪声，并改善皮下脂肪层的可视性。最后，我们使用Rosiniquests阈值和随机样本共识边界检测来提取胖边界。我们的方法适用于9位人类受试者的上轨，大腿和肱三头肌体内获得的36个样品。在我们的研究中，观察到手动和自动超声测量之间的相关性很高（在所有身体部位r> 0.7），皮褶卡尺和自动超声测量之间的相关性很高（在所有身体部位r> 0.7）。

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