基于局部Radon变换和卡尔曼滤波的超声图像肌束方向自动跟踪方法

doi:10.3969/j.issn.0258-8021. 2016. 02.003

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Abstract Ultrasound imaging is a noninvasive, realtime and convenient imaging method, which has been widely applied in analysis of human muscle contraction. So far manual operation is commonly used in clinical applications to extract morphological parameters from ultrasound image, however, may bring outcomes such as subjective, time-consuming and low repetitive. In this paper, an automatic method is proposed to calculate and track the fascicle orientation in sequences of ultrasound images. We constrained mutual information-based free-form deformation algorithm to automatically detect reading of interest. Then the detected results were projected based on local Radon transform. Then the Kalman filter image processing technique was applied to predict and track the next frame change of fascicle orientation. Six subjects participated in the walking experiment. We collected the dynamic ultrasound images from the medial gastrocnemius muscle during the process and calculated the muscle fascicle orientation using the proposed method. Experimental results showed that the proposed automatic detection method achieved better robustness. Compared with the manual measurement, the average correlation coefficient was 0.92±0.02, and the average error was 0.30°±0.62°. To some extent, the proposed method can replace the manual measurement, presenting a significant advantage especially when dealing with a large number of ultrasound data.

Key words： ultrasonography fascicle orientation radon transform Kalman filter

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	Articles by authors
	Wen Huiying¹Yang Xiaojuan¹Guo Yanrong¹Zhang Shuai²Zhang Zhiguo²Wang Tianfu¹Chen Siping¹Chen Xin^1*

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Wen Huiying¹Yang Xiaojuan¹Guo Yanrong¹Zhang Shuai²Zhang Zhiguo²Wang Tianfu¹Chen Siping¹Chen Xin^{1*
. Automatic Tracking of Muscle Fascicle Orientation in Ultrasound Images: A Novel Approach Based on Local Radon Transform and Kalman Filter[J]. journal1, 2016, 35(2): 141-147.}

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021. 2016. 02.003 OR http://cjbme.csbme.org/EN/Y2016/V35/I2/141

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