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《浙江大学学报(英文版)》 2005-11
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Liver fibrosis identification based on ultrasound images captured under varied imaging protocols

CAO Gui-tao 1, SHI Peng-fei 1, HU Bing 2 (1Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200030, China) (2Department of Ultrasound in Medicine, Shanghai Sixth Hospital, Shanghai Jiao Tong University, Shanghai 200233, China)  
Diagnostic ultrasound is a useful and noninvasive method in clinical medicine. Although due to its qualitative, sub- jective and experience-based nature, ultrasound image interpretation can be influenced by image conditions such as scanning frequency and machine settings. In this paper, a novel method is proposed to extract the liver features using the joint features of fractal dimension and the entropies of texture edge co-occurrence matrix based on ultrasound images, which is not sensitive to changes in emission frequency and gain. Then, Fisher linear classifier and support vector machine are employed to test a group of 99 in-vivo liver fibrosis images from 18 patients, as well as other 273 liver images from 18 normal human volunteers.
【CateGory Index】: R575.2;
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【References】
Chinese Journal Full-text Database 1 Hits
1 LIU Jin-zhu1,WANG Jiang-he2,HONG Hui-wen2,LIU Yan-ling2,MIN Le-quan1,3 1.School of Information Engineering,University of Science and Technology Beijing,Beijing 100083,China2.Hepatology Department,Xiyuan Hospital of China Academy of Chinese Medical Sciences,Beijing 100091,China3.School of Applied Science,University of Science and Technology Beijing,Beijing 100083,China;Classification method of ultrasonic images of fatty livers based on threshold segmentation[J];计算机工程与应用;2010-36
【Co-references】
Chinese Journal Full-text Database 5 Hits
1 QUAN Wei-wei1, WU Bin2, Zhang Ji-hua3(School of Information Engineering, SWUST, Mianyang,Sichuan 621002,China)Quan Weiwei(School of Information Engineering, SWUST, Mianyang,Sichuan 621002,China)Wu Bin(Department of function, Petroleum hospital of the northChina, Hebei 062550,China)Zhang Jihua;Research on B-Scan Ultrasonic Image Recognition of Fatty Liver Based on Artificial Neural Network[J];微计算机信息;2007-27
2 CHEN FEI;The application research of Neural Network for classifying the ultrasonic liver image[J];微计算机信息;2007-12
3 CAO Gui-tao 1, SHI Peng-fei 1, HU Bing 2 (1Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200030, China) (2Department of Ultrasound in Medicine, Shanghai Sixth Hospital, Shanghai Jiao Tong University, Shanghai 200233, China);Liver fibrosis identification based on ultrasound images captured under varied imaging protocols[J];Journal of Zhejiang University Science;2005-11
4 LIN Jiang-li~(1),WANG Xiao-yi~(1),LI De-yu~(2),WANG Tian-fu~(1),ZHENG Chang-qiong~(1),CHENG Yin-rong~(3)(1.Dept. of Biomedical Eng., Sichuan Univ., Chengdu 610065, China;2.Central. of Biomedical Eng., Sichuan Univ., Chengdu 610065, China;3.Ultrasonic office of Chengdu First People's Hospital,Chengdu 610016, China);Feature Extraction for B-scan Fatty Liver Image[J];四川大学学报(工程科学版);2005-01
5 WANG Xiao-yi,LIN Jiang-li,LI De-yu,WANG Tian-fu,ZHENG Chang-qiong,CHENG Yin-rong Department of Biomedical Engineering, Sichuan University, Chengdu 610065, China;B-Scan Ultrasonic Image Recognition of Fatty Liver Based on Texture Analysis[J];航天医学与医学工程;2004-02
【Secondary References】
Chinese Journal Full-text Database 1 Hits
1 PENG Guo-hua;WU Cai-yi;WU Jian-hui;LUAN Qiang-hou;School of Life Science and Technology, University of Electronic and Technology of China;Sun Yat-sen University School of Mathematics and Computational Science;Ruichao Electronic Technology Co.,Ltd;;Grading Diagnosis of Rats' Fatty Liver Tissue Based on Ultrasonic Radiofrequency Signal[J];现代生物医学进展;2013-25
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