Paper
1 April 2016 Development of estimation system of knee extension strength using image features in ultrasound images of rectus femoris
Hiroki Murakami, Tsuneo Watanabe, Daisuke Fukuoka, Nobuo Terabayashi, Takeshi Hara, Chisako Muramatsu, Hiroshi Fujita
Author Affiliations +
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.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hiroki Murakami, Tsuneo Watanabe, Daisuke Fukuoka, Nobuo Terabayashi, Takeshi Hara, Chisako Muramatsu, and Hiroshi Fujita "Development of estimation system of knee extension strength using image features in ultrasound images of rectus femoris", Proc. SPIE 9790, Medical Imaging 2016: Ultrasonic Imaging and Tomography, 979012 (1 April 2016); https://doi.org/10.1117/12.2214843
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KEYWORDS
Ultrasonography

Data modeling

Fourier transforms

Medical imaging

Edge detection

Error analysis

Image compression

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