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Medical image segmentation using improved FCM

Science china(Information Sciences) 2012年第5期55卷 1052-1061页

作者： ZHANG XiaoFeng 1,2,ZHANG CaiMing 1,3,4,TANG WenJing 1,2 & WEI ZhenWen 1 1 School of Computer Science and technology,shandong University,jinan 250101,china 2 School of Information and Electrical Engineering,Ludong University,Yantai 264025,china 3 School of Computer Science and technology,shandong University of Finance and Economics,jinan 250014,china 4 shandong province key lab of digital media technology,jinan 250014,china 1. School of Computer Science and technology Shandong University Jinan 250101 China2. School of Information and Electrical Engineering Ludong University Yantai 264025 China3. School of Computer Science and Technology Shandong University of Finance and Economics Jinan 250014 China4. Shandong Province Key Lab of Digital Media Technology Jinan 250014 China

Image segmentation is one of the most important problems in medical image processing,and the existence of partial volume effect and other phenomena makes the problem much more *** C-means,as an effective tool to deal with PVE,however,is faced with great challenges in *** at this,this paper proposes one improved FCM algorithm based on the histogram of the given image,which will be denoted as HisFCM and divided into two *** first phase will retrieve several intervals on which to compute cluster centroids,and the second one will perform image segmentation based on improved FCM *** with FCM and other improved algorithms,HisFCM is of much higher efficiency with satisfying *** on medical images show that HisFCM can achieve good segmentation results in less than 0.1 second,and can satisfy real-time requirements of medical image processing.

关键词： FCM histogram image segmentation medical image processing

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Research and Practice on New Interactive Teaching Model Based on Constructivist Learning Theory

Research and Practice on New Interactive Teaching Model Base...

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2008 IEEE International Symposium on IT in Medicine and Education(ITME 2008)

作者： Zhenzhong Xu 1 2 Huijian Han 1 2 Yunfeng Zhang 1 2 Caiming Zhang 1 2 1 School of Computer Science & technology shandong Economic University jinan 250014 china 2 shandong Prov.key lab of digital media technology jinan 250014 china

A new interactive information transmission model of teaching based on the constructivist learning theory is created and studied in this *** to the different classification of knowledge,how to play the different functions of the information transmission channels? How to apply the information technology in the interactive teaching model? Those problems are *** application principles and methods of the information technology are *** Example is give to show the application of the interactive teaching model in practical teaching.

关键词： constructivist learning theory interactive teaching information transmission model multimedia technology network technology

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Estimation on principal component of multi-collinearity Gauss-Markov model based on minimum description length

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中国有色金属学会会刊：英文版 2005年第S1期15卷 153-155页

作者： SHI Yu-feng~(1, 2) (1. shandong University of technology, Zibo 255049, china 2. key laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University, Wuhan 430079, china) shandong Univ Technol Zibo 255049 Peoples R China Wuhan Univ Minist Educ Key Lab Geospace Environm & Geodesy Wuhan 430079 Peoples R China

Gauss-Markov model is frequently used in data analysis; the analysis and estimation of its parameters is always a hot issue. Based on the information theory and from the viewpoint of optimal information on description—minimum description length, this paper discusses a case: where there is multi-collinearity in the coefficient matrix, principal component estimation is used to estimate and select the original parameters, so as to reduce its multi-collinearity and improve its credibility. From the viewpoint of minimum description length, this paper discusses the approach of selecting principal components and uses this approach to solve a practical problem.

关键词： minimum description length Gauss-Markov model multi-collinearity principal component estimation

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