Multiplicative gradient based edge detection method for medical ultrasound image" /> Multiplicative gradient based edge detection method for medical ultrasound image" /> Multiplicative gradient based edge detection method for medical ultrasound image" /> 基于乘性梯度的医学超声图像边缘检测算法
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JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE)
    
Multiplicative gradient based edge detection method for medical ultrasound image
GONG Xiao-hong1, ZHENG Yin-fei1, QIN Jia-le2, ZHOU Hao1
1.Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou 310027, China; 2. Department of Ultrasound, Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou 310006, China
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Abstract  

An accurate and fast edge detection method for medical ultrasound images was proposed based on a modified multiplicative gradient (MG) operator and the traditional Canny. The dimension of the template of the MG operator was increased to improve the performance in weak edge detecting. The results of Canny and MG operators were combined to improve the accuracy of the edge detection. The proposed method was evaluated based on simulated and in vivo ultrasound images. Experimental results showed that the accuracy of the proposed method was more than 75% for different speckle noise level. The results of the edge detection can be obtained in real-time by using the proposed method.



Published: 01 October 2014
CLC:  TP 242  
Cite this article:

GONG Xiao-hong, ZHENG Yin-fei, QIN Jia-le, ZHOU Hao.

Multiplicative gradient based edge detection method for medical ultrasound image
. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2014, 48(10): 1871-1878.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2014.10.023     OR     http://www.zjujournals.com/eng/Y2014/V48/I10/1871


基于乘性梯度的医学超声图像边缘检测算法

通过改进传统乘性梯度(MG)算子,并结合Canny算子的处理结果,准确、快速地提取了医学超声图像的边缘.通过提升乘性梯度算子模板的维度,提高对弱边缘的检测能力;综合考虑乘性梯度算子和Canny算子的运算结果,提高边缘检测的准确度.为了验证该算法的有效性,对仿真及在体超声图像进行边缘提取实验,将结果与其他抗噪性较好的边缘检测方法进行对比.实验结果表明:对于含有不同强度斑点噪声的超声图像,该算法的边缘检测准确度可达75%以上,具有较好的实时性,适用于对医学超声图像进行快速、准确的边缘检测.

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