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An algorithm for segmentation of lung ROI by mean-shift clustering combined with multi-scale HESSIAN matrix dot filtering

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Journal of Central South University 2012年第12期19卷 3500-3509页

作者：魏颖李锐杨金柱赵大哲 School of Information Science and Engineering Northeastern University Key Laboratory of Medical Imaging Calculation of Ministry of Education(Northeastern University)

A new algorithm for segmentation of suspected lung ROI(regions of interest)by mean-shift clustering and multi-scale HESSIAN matrix dot filtering was *** image was firstly filtered by multi-scale HESSIAN matrix dot filters,round suspected nodular lesions in the image were enhanced,and linear shape regions of the trachea and vascular were ***,three types of information,such as,shape filtering value of HESSIAN matrix,gray value,and spatial location,were introduced to feature *** kernel function of mean-shift clustering was divided into product form of three kinds of kernel functions corresponding to the three feature ***,bandwidths were calculated adaptively to determine the bandwidth of each suspected area,and they were used in mean-shift clustering *** results show that by the introduction of HESSIAN matrix of dot filtering information to mean-shift clustering,nodular regions can be segmented from blood vessels,trachea,or cross regions connected to the nodule,non-nodular areas can be removed from ROIs properly,and ground glass object(GGO)nodular areas can also be *** the experimental data set of 127 different forms of nodules,the average accuracy of the proposed algorithm is more than 90%.

关键词： HESSIAN matrix multi-scale dot filtering mean-shift clustering segmentation of suspected areas lung computer-aideddetection/diagnosis

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User-controllable mesh segmentation using shape harmonic signature

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Progress in Natural Science:Materials International 2009年第4期19卷 471-478页

作者： Yongwei Miao a,b, Jieqing Fenga, Jinrong Wanga,c, Xiaogang Jin a a State Key Laboratory of CAD & CG, Zhejiang University, Hangzhou 310027, China b College of Science, Zhejiang University of Technology, Hangzhou 310032, China c Information Science & Engineering School, Hangzhou Normal University, Hangzhou 310036, China State Key Laboratory of CAD & CG Zhejiang University Hangzhou 310027 China College of Science Zhejiang University of Technology Hangzhou 310032 China Information Science & Engineering School Hangzhou Normal University Hangzhou 310036 China

Due to different shape modeling applications, partitioning a given complex 3D mesh model into some patches or meaningful subparts is one of the fundamental problems in digital geometry processing. By using the high-dimensional mean-shift clustering scheme in shape signature space, a new method is proposed which can generate user-specified segmentation results automatically for different applications. The shape signature is composed of mesh geometric attributes and its spectral harmonics. The latter one can reflect mesh frequency spectrum information. The low frequency components are essential for semantics-oriented segmentation, while the high frequency components are important for purely geometry-oriented segmentation. The effects of the proposed method are demonstrated by several examples.

关键词： Mesh segmentation Manifold harmonic analysis Shape harmonic signature mean-shift clustering

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The Application of mean-shift Cluster in Residential Appliance Identification

The Application of Mean-shift Cluster in Residential Applian...

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第三十届中国控制会议

作者： WANG Zhenyu,ZHENG Guilin Department of Automation,Wuhan University,Wuhan 430072,P.R.China

This paper proposes the application flow of mean-shift clustering in NILM *** raw data is extracted by meter which install on the main electric entrance of the resident,the mean-shift clustering is based on the data after events detector processing,and the result of clustering is used as input data of final identification.A actual residential trail is given to show the clustering is available in the NILM system.

关键词： NILM mean-shift clustering Residential appliance identification

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