Development of estimation system of knee extension strength using image features in ultrasound images of rectus femoris

Hiroki Murakami, Tsuneo Watanabe, D. Fukuoka, N. Terabayashi, T. Hara, C. Muramatsu, H. Fujita
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引用次数: 1

Abstract

The word "Locomotive syndrome" has been proposed to describe the state of requiring care by musculoskeletal disorders and its high-risk condition. Reduction of the knee extension strength is cited as one of the risk factors, and the accurate measurement of the strength is needed for the evaluation. The measurement of knee extension strength using a dynamometer is one of the most direct and quantitative methods. This study aims to develop a system for measuring the knee extension strength using the ultrasound images of the rectus femoris muscles obtained with non-invasive ultrasonic diagnostic equipment. First, we extract the muscle area from the ultrasound images and determine the image features, such as the thickness of the muscle. We combine these features and physical features, such as the patient’s height, and build a regression model of the knee extension strength from training data. We have developed a system for estimating the knee extension strength by applying the regression model to the features obtained from test data. Using the test data of 168 cases, correlation coefficient value between the measured values and estimated values was 0.82. This result suggests that this system can estimate knee extension strength with high accuracy.
基于股直肌超声图像特征的膝关节伸展强度估计系统的开发
“机车综合征”一词已被提出用来描述肌肉骨骼疾病及其高危状况需要护理的状态。膝关节伸展强度降低被认为是危险因素之一,评估时需要准确测量膝关节伸展强度。使用测功机测量膝关节伸展强度是最直接和定量的方法之一。本研究旨在开发一种利用非侵入性超声诊断设备获得的股直肌超声图像来测量膝关节伸展强度的系统。首先,我们从超声图像中提取肌肉区域,并确定图像特征,如肌肉的厚度。我们将这些特征与患者身高等身体特征结合起来,从训练数据中构建膝关节伸展力量的回归模型。我们开发了一个系统,通过将回归模型应用于从测试数据中获得的特征来估计膝关节伸展强度。使用168例试验数据,实测值与估计值的相关系数值为0.82。结果表明,该系统可以较准确地估计膝关节伸展强度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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