Research Of Denoising Algorithm Of Ultrasound Image And Its Applications In Assessment Of Muscle Functions

This paper mainly focuses on ultrasound images of muscle of human body.Compared with other medical imaging techniques, medical ultrasound image hasproperties of low-cost, real time, fast, non-radiative and non-invasive. It has asignificant role in such well-developed medical imaging techniques. Hence,quantitative ultrasound is widely applied in a clinical application, the assessment ofmuscle functions.However, due to the random disturbance of electronic devices in ultrasonicimaging system, and the effect of the environment, in the process of acquiring image,there will be some noises and distortions which may influence image quality. So weshould denoise the image before diagnostic analysis. In this paper, we first study theclassical bilateral filter and some improved algorithms, aiming at the characteristics ofultrasound image, we then propose an improved fast adaptive bilateral filter to denosiethe ultrasound images. We assess the proposed algorithm in terms of run time andaccuracy. Experiment results show that this algorithm has a low computationcomplexity and achieves a promising denoising effectiveness, compared with theclassical bilateral filter.Muscle thickness, a quantification which can effectively reflect the muscleactivities during muscle contraction, is an important measure for musculoskeletalstudies using ultrasonography. The traditional manual operation to read musclethickness is subjective and time-consuming, therefore a number of studies havefocused on the automatic estimation of muscle thickness. In this paper, based on theexisting research findings, we propose a method of automatic muscle thicknessestimation based on Hough transformation. Experiment results show that this methodcan estimate the muscle thickness automatically, fast and precisely.