中文摘要：

为了减少利用超声图像进行肝硬化诊断时临床医师的主观性对诊断准确性的影响，首次提出了一种利用Gabor变换和LBP特征融合的方法对肝硬化和正常肝脏进行识别。首先对原始肝脏样本分别提取其Gabor特征和LBP特征，然后将这两种特征进行融合，得到鲁棒性较强的特征，并利用C—SVM进行训练和分类。该方法克服了超声环境下肝脏图像所受的光照影响、边缘模糊，以及在尺度因素的影响下，其病变区域与正常区域的纹理用肉眼很难区分等困难，对正常肝脏和肝硬化的识别精度达到了100％，说明提出的方法可有效提高在超声环境下对肝硬化的诊断准确率，减少临床医师主观性的影响。

英文摘要：

In order to reduce the impact of subjectivity by clinician in diagnosing the liver cirrhosis using the ultrasound images, a method that utilizes the feature fusion of Gabor transform and LBP feature to recognize cirrhosis and normal liver is proposed. Firstly, Gabor feature and LBP feature of the original liver samples are extracted, then a fusion of these two features is made, and the strong robust feature is obtained. Finally, the training and classification will be accomplished by C-SVM. The proposed method has overcome some difficulties under the ultrasound circumstances such as the influences of illumination, the blurring of edges, and it is hard to distinguish the textures between the lesion region and normal region with naked eye due to the scale factor. The best recognition rate acquired by the proposed method is 100% , which indicates that the proposed method can improve the recognition rate of liver cirrhosis under the ultrasound circumstances effectively and reduce the impact of subjectivity of clinician.