Computer Engineering and Applications ›› 2013, Vol. 49 ›› Issue (14): 170-173.

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Robust and automated approach to ultrasonic liver image classification

LAN Yihua1, REN Haozheng1, ZHANG Yong1, LI Ming2   

  1. 1.School of Computer Engineering, Huaihai Institute of Technology, Lianyungang, Jiangsu 222005, China
    2.Department of Imaging Processing Business, Beijing E-COM Technology CO., LTD., Beijing 100176, China
  • Online:2013-07-15 Published:2013-07-31

一种稳健的脂肪肝超声图像自动分类方法

兰义华1,任浩征1,张  勇1,李  明2   

  1. 1.淮海工学院 计算机工程学院,江苏 连云港 222005
    2.北京友通上昊科技有限公司 图像处理事业部,北京 100176

Abstract: When using computer aided detection system to detect fatty liver on ultrasonic liver image, ROI(Region Of Interest) selected by doctors leads to uncertain classification results. To avoid the influence which caused by artificial factor, an approach can get a robustness, ROI independent result for fatty liver detection is proposed by using image decomposition technique. Each liver image is decomposed into a cartoon part and a texture part by a variation method. The cartoon part is used to indicate the location of ROI while texture feature will be calculated in the according texture part. Experimental results show that the texture information extracted from the decomposition texture image has better classification accuracy than the one extracted from the original ultrasonic liver image.

Key words: fatty liver, ultrasonic image, image decomposition, cartoon image, texture image

摘要: 进行脂肪肝超声图像的计算机辅助检测时,由医生手工选择感兴趣区域使得分类结果具有不确定性。为了避免人为因素对检测结果的影响,构造了一种利用图像分解技术确定ROI的算法,使得检测结果具有很强的稳健性。通过变分的方法把输入超声图像分解为纹理图和卡通图两部分,利用卡通图上的强度信息确定ROI,在纹理图上计算对应ROI的纹理特征。试验表明,相对于直接从超声图像上提取纹理信息,从分解后的纹理图像上提取的纹理信息有更好的分类效果。

关键词: 脂肪肝, 超声图像, 图像分解, 卡通图, 纹理图