基于超声射频信号的肩袖损伤识别

肩袖撕裂是一种常见疾病，超声已被认为是该疾病首选的检查方法，但撕裂后的血肿充填易导致常规超声扫查的假阴性，本文提出一种基于超声原始射频(Radio frequency, RF)信号的肩袖撕裂识别方法。首先将B超诊断仪设置在二次谐波扫描模式，扫描和存储组织的原始RF数据。其次对一帧RF数据进行带通滤波并在这帧RF数据中选取感兴趣和参考区域；然后计算感兴趣和参考区域内每条扫描线上每一个或数个周期内二次谐波的均方根值。再用Kolmogorov-Smirnov检验把各区域内每条扫描线上的均方根值与参考区域的进行比较，计算相应p值。最后将感兴趣区域的算术平均p值除以参考区域的算术平均p值，得到相对p值。本方法解决了当前B超检查中识别复杂生物组织异常主观性强和需要有丰富临床经验的问题，测量准确、容易实施。

Diagnosis of Rotator Cuff Tear Based on Ultrasonic Radio-Frequency Signals

Rotator cuff tear is a kind of frequently-occurring disesae,and ultrasonography is the prefferred examination method for the disease,but the organization of hematoma in the nidus leads to false-negative in most cases.A new nonlinear approach based on statistical analysis of ultrasound radio-frequency(RF) signals is developed for identifying the lesion to improve the diagnostic accuracy. Firstly, the raw RF data is scanned and saved in the second harmonic mode,then the region of interest(ROI) and reference region (RR) are selected in one frame by applying the band-pass filter. The root-mean-square value of second harmonic in one or more cycles within ROI and RR are calculated and compared by Kolmogorov-Smirnow test for the p-value.The relative p-value is estimated by comparing the ROI and RR. The proposed method solves the problems of high subjectivity in identifying complex tissue and requisiting rich clinical experience in the ultrasound examination with accurate measurement and easy implement.