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《Journal of Fudan University》 2001-01
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Two Methods of Non-invasive Automatic Classification for the Placental Function Using the Ultrasound Image

MA Xiang1, WANG Yuan-yuan1, WANG Wei-qi1, CHANG Cai2, LIU Zhi2 (1. Department of Electronic Engineering, Fudan University, Shanghai 200433, China; 2. Shanghai Obstetrics and Gynecology Hospital, Shanghai 200011, China)  
An non-invasive automatic classification method is proposed based on the B model ultrasound images of the placenta of various gestational weeks. First of all several characteristic parameters are extracted from the images. Then together with the grading results of the doctor, the rules of automatic classification are established by two methods, the fuzzy classification and the quantification theory. Finally the performance of these two methods is compared with the clinical application. The results show that the non-invasive automatic classification method of the placental function can be feasibly used in clinic.
【Fund】: 国家自然科学基金资助项目! (3980 0 137)
【CateGory Index】: TB559
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【Co-references】
Chinese Journal Full-text Database 8 Hits
1 Dong Jing~1,Zhao Xiao-hui~1,Ying Na~2(1.College of Communication Engineering,Jilin University,Changchun 130012,China;2.College of Communication Engineering,Hangzhou Dianzi University,Hangzhou 310018,China);Pitch detection algorithm based on dyadic wavelet transforms[J];Journal of Jilin University(Engineering and Technology Edition);2006-06
2 Yu Haipeng Liu Yixing Zhang Bin Li Yongfeng (Material Science and Engineering College,Northeast Forestry University Harbin 150040);Application of Spatial Gray Level Cooccurrence Matrix in Wood Surface Texture Quantitative Analysis[J];Scientia Silvae Sinicae;2004-06
3 Zhu Mei_Lin, Liu Xiang_Dong, Chen Shi_Fuiversity, Nanjing, 210093,China);Solving the Problem of Multi-class Pattern Recognition with Sphere-structured Support Vector Machines[J];Journal of Nanjing University (Natural Sciences);2003-02
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];Journal of Sichuan University (Engineering Science Edition);2005-01
5 LI Pan-chi, XU Shao-hua (Institute of Computer Science and Engineering, Daqing Petroleum College, Daqing 163318, China);Support vector machine and kernel function characteristic analysis in pattern recognition[J];Computer Engineering and Design;2005-02
6 MAO Jian-fei,YANG Xu-hua,TIAN Xian-zhong (Information Engineering Institute,Zhejiang University of Technology,Hangzhou 310032);The Study of Automatic Classification for Ultrasound Placenta Images Based on Adaptive Multiple Neural Networks[J];Journal of Image and Graphics;2006-07
7 LIU Zhi, CHANG Cai, MA Xiang, et al. Department of Ultrasound Diagnostics, Obstetric & Gynecologic Hospital,Medical Centre of Fudan University, Shanghai 200011, China;Primary study on automatic ultrasonic grading of placenta[J];Chinese Journal of Uitrasonography;2000-12
8 MA Xiang,WANG Yuan-yuam,WANG Wei-qi,CHANG Cai,LIU ZHi(1.Department of Electronic Engineering,Fudan University,Shanghai 200433;2.Obstetrics and Gynecology Hospital,Shanghai Medical University,Shanghai 200011);EYALUATING THE PLACENTAL FUNCTION DURING GESTATIONAL PERIOD USING THE FRACTAL CHARACTER OF ULTRASOUND IMAGES[J];Chinese Journal of Biomedical Engineering;2002-06
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