政府购买社会服务是否"物有所值"已受到社会各界的关注。文章以社会投资回报分析法(SROI,Social Return of Investment)为蓝本,对一个项目实例进行初步评估分析。研究发现,SROI可较全面描述利益相关方在项目中的投入、产出及...政府购买社会服务是否"物有所值"已受到社会各界的关注。文章以社会投资回报分析法(SROI,Social Return of Investment)为蓝本,对一个项目实例进行初步评估分析。研究发现,SROI可较全面描述利益相关方在项目中的投入、产出及成果,并将项目成本、成效和投资回报率进行量化,以检验服务项目是否创造效率、质量、成效和公平的预设价值。但是,SROI亦面临操作成本和成效统计复杂、难以收集相关评价数据和成效定价困难等方面限制。最后,文章建议借鉴SROI思维与技术,开发包涵多元价值属性的评价准则与相关分析工具、搭建公共服务评议平台,构建政府购买社会服务项目的评估体系。展开更多
A new algorithm for segmentation of suspected lung ROI(regions of interest)by mean-shift clustering and multi-scale HESSIAN matrix dot filtering was proposed.Original image was firstly filtered by multi-scale HESSIAN ...A new algorithm for segmentation of suspected lung ROI(regions of interest)by mean-shift clustering and multi-scale HESSIAN matrix dot filtering was proposed.Original 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 suppressed.Then,three types of information,such as,shape filtering value of HESSIAN matrix,gray value,and spatial location,were introduced to feature space.The kernel function of mean-shift clustering was divided into product form of three kinds of kernel functions corresponding to the three feature information.Finally,bandwidths were calculated adaptively to determine the bandwidth of each suspected area,and they were used in mean-shift clustering segmentation.Experimental 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 segmented.For the experimental data set of 127 different forms of nodules,the average accuracy of the proposed algorithm is more than 90%.展开更多
文摘政府购买社会服务是否"物有所值"已受到社会各界的关注。文章以社会投资回报分析法(SROI,Social Return of Investment)为蓝本,对一个项目实例进行初步评估分析。研究发现,SROI可较全面描述利益相关方在项目中的投入、产出及成果,并将项目成本、成效和投资回报率进行量化,以检验服务项目是否创造效率、质量、成效和公平的预设价值。但是,SROI亦面临操作成本和成效统计复杂、难以收集相关评价数据和成效定价困难等方面限制。最后,文章建议借鉴SROI思维与技术,开发包涵多元价值属性的评价准则与相关分析工具、搭建公共服务评议平台,构建政府购买社会服务项目的评估体系。
基金Projects(61172002,61001047,60671050)supported by the National Natural Science Foundation of ChinaProject(N100404010)supported by Fundamental Research Grant Scheme for the Central Universities,China
文摘A new algorithm for segmentation of suspected lung ROI(regions of interest)by mean-shift clustering and multi-scale HESSIAN matrix dot filtering was proposed.Original 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 suppressed.Then,three types of information,such as,shape filtering value of HESSIAN matrix,gray value,and spatial location,were introduced to feature space.The kernel function of mean-shift clustering was divided into product form of three kinds of kernel functions corresponding to the three feature information.Finally,bandwidths were calculated adaptively to determine the bandwidth of each suspected area,and they were used in mean-shift clustering segmentation.Experimental 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 segmented.For the experimental data set of 127 different forms of nodules,the average accuracy of the proposed algorithm is more than 90%.
