Abstract
Ultrasound myograph (SMG) is a real-time and dynamic acquisition of muscle structure parameter changes by recording ultrasound images of muscle contraction through an ultrasound instrument. Muscle parameters are essential for judging whether the muscle and the human body are healthy. In order to solve the problem of muscle fiber tracking in a sequence of ultrasound muscle images, we propose a method to track the direction of muscle fibers automatically based on the improved Kalman filter. Firstly, the measurement value of the muscle fiber direction is obtained by introducing a reference line into the ultrasound muscle image based on deep learning. Secondly, the framework of a Kalman filter is improved by introducing a set of neural units. Finally, the optimal estimated value of muscle fiber direction is obtained by combining the measured value with the improved Kalman filter. It is verified by conducting experiments where the result obtained by our proposed method is closer to the manually labeled value compared with the original measurement method, and the root mean square error is reduced by about 10%.
Highlights
Ultrasound medicine includes ultrasound diagnostics, ultrasound therapy, and biomedical ultrasound engineering
In the previous work reported in [24], a reference line is introduced into the image of the muscle fiber, and the ResNet-50 deep learning network [27] is used to judge the relationship between the muscle fibers and the line by using sub-images
In order to verify the effectiveness of the method proposed in this paper, we compare it with the extended Kalman filter (EKF) and unscented Kalman Filter(UKF)
Summary
Ultrasound medicine includes ultrasound diagnostics, ultrasound therapy, and biomedical ultrasound engineering. For doctors and patients, ultrasound technology is easy to operate, non-invasive, reusable, and relatively inexpensive, and it can clearly observe the chest, abdomen, blood vessels, muscles, etc It is widely used in the diagnosis of major diseases and the analysis of human movement functions [1]. It uses an ultrasound instrument to record ultrasound images generated during muscle contraction to dynamically obtain changes in muscle structure parameters in real time. This method greatly reduces the measurement interference caused by adjacent muscles, and a more comprehensive exploration of the deep muscles of the human body can be conducted
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