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使用 Gabor 滤波器组方法对肌肉超声中的高回声区域进行纵向增强:半自动肌纤维方向估计的准备。

Longitudinal enhancement of the hyperechoic regions in ultrasonography of muscles using a Gabor filter bank approach: a preparation for semi-automatic muscle fiber orientation estimation.

机构信息

Department of Health Technology and Informatics and the Research Institute of Innovative Products and Technologies, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, P.R. China.

出版信息

Ultrasound Med Biol. 2011 Apr;37(4):665-73. doi: 10.1016/j.ultrasmedbio.2010.12.011. Epub 2011 Mar 3.

Abstract

In this study, to complement our previously proposed method for estimating muscle fiber orientation, the Gabor filter bank (GF) technique was applied to sonograms of the biceps and forearm muscles to longitudinally enhance the coherently oriented and hyperechoic perimysiums regions. The method involved three steps: orientation field estimation, frequency map computation and Gabor filtering. The method was evaluated using a simulated image distorted with multiplicative speckle noises where the "muscles" were arranged in a bipennate fashion with an "aponeurosis" located in the middle. After enhancement using the GF approach, most of the original hyperechoic bands in the simulated image could be recovered. The proposed method was also tested using a group of biceps and forearm muscle sonograms collected from healthy adult subjects. Compared with the sonograms without enhancement, the enhanced images led to the detection of more linear patterns including muscle fascicles and smaller angle differences compared with the mean of manual results from two operators, therefore, were better prepared for the automatic estimation of muscle fiber orientation. The proposed method has the potential of assisting in the visualization of strongly oriented patterns in skeletal muscle sonograms as well as in the semi-automatic estimation of muscle fiber orientations.

摘要

在这项研究中,为了补充我们之前提出的估计肌肉纤维方向的方法,应用了 Gabor 滤波器组 (GF) 技术对二头肌和前臂肌肉的超声图像进行处理,以纵向增强具有相干取向和高回声的肌周区域。该方法包括三个步骤:方向场估计、频率图计算和 Gabor 滤波。该方法使用经过乘法斑点噪声干扰的模拟图像进行评估,其中“肌肉”呈双羽状排列,“腱膜”位于中间。使用 GF 方法增强后,大部分原始模拟图像中的高回声带都可以被恢复。该方法还使用从健康成年受试者收集的一组二头肌和前臂肌肉超声图像进行了测试。与未经增强的超声图像相比,增强后的图像能够检测到更多的线性模式,包括肌肉束和与两名操作人员的手动结果平均值相比更小的角度差异,因此,更适合肌肉纤维方向的自动估计。该方法有可能有助于可视化骨骼肌肉超声图像中的强定向模式,以及半自动估计肌肉纤维方向。

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