| 陈兴,丁亚军,钱盛友,郭燕.基于超声图像的生物组织损伤判定方法研究[J].电子测量与仪器学报,2019,33(1):171-176 |
| 基于超声图像的生物组织损伤判定方法研究 |
| Research on identification method of biological tissue lesion based on ultrasound images |
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| DOI： |
| 中文关键词: 高强度聚焦超声 B超图像 FCM聚类 灰度梯度共生矩阵 组织损伤 |
| 英文关键词:high intensity focused ultrasound(HIFU) ultrasound image FCM clustering gray level gradient co occurrence matrix biological tissue lesion |
| 基金项目:国家自然科学基金(11774088，11474090，61502164）、湖南省自然科学基金（2016JJ3090）资助项目 |
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| 中文摘要: |
| 针对高强度聚焦超声(HIFU)治疗的生物组织变性监测，提出一种基于超声图像灰度 梯度共生矩阵和模糊C均值聚类(FCM)的生物组织损伤判定方法。首先对新鲜离体猪肉组织进行高强度聚焦超声辐照，对采集到的超声图像进行预处理后提取减影图像的灰度 梯度共生矩阵的灰度熵、混合熵作为组织损伤判定的表征参数，再使用FCM聚类方法对特征参数进行聚类判别。实验结果表明，结合灰度熵与混合熵的多参数判定比单参数灰度熵、混合熵判定的识别率更高，相比灰度均值与小波系数结合方法，其识别率提高323％。可以更准确地判定在高强度聚焦超声治疗过程中的组织损伤状况。如进一步与无损测温相结合，可进一步提高高强度聚焦超声的疗效。 |
| 英文摘要: |
| In order to monitor the biological tissue lesion when using HIFU to treat, a method that biological tissue lesion identification based on ultrasound image by Graylevel gradient co occurrence matrix and FCM clustering is proposed. First, obtaining ultrasound images of fresh pork tissue which irradiated by high intensity focused ultrasound and extract parameters of Gray level gradient co occurrence matrix after preprocessing. The parameters of gray entropy and entropy of mixing are the characterization parameter of identification of biological tissue lesion. And then using FCM clustering method to analysis. The results show that the rate of identification is higher when combining Gray entropy with entropy of mixing to identify biological tissue lesion than signal parameter, which is 332 percentage more than that gray average and wavelet transform coefficient method. Thus,this method can better identify tissue lesion in the course of HIFU treatment. The method is helpful to improve the efficacy of HIFU treatment, relating the noninvasive temperature measurement with tissue lesion identification further. |
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