This paper presents a fully automatic segmentation method of liver CT scans using fuzzy c-mean clustering and level set. First, the contrast of original image is enhanced to make boundaries clearer;second, a spatial f...This paper presents a fully automatic segmentation method of liver CT scans using fuzzy c-mean clustering and level set. First, the contrast of original image is enhanced to make boundaries clearer;second, a spatial fuzzy c-mean clustering combining with anatomical prior knowledge is employed to extract liver region automatically;thirdly, a distance regularized level set is used for refinement;finally, morphological operations are used as post-processing. The experiment result shows that the method can achieve high accuracy (0.9986) and specificity (0.9989). Comparing with standard level set method, our method is more effective in dealing with over-segmentation problem.展开更多
This paper proposes a clustering technique that minimizes the need for subjective human intervention and is based on elements of rough set theory （RST）. The proposed algorithm is unified in its approach to clusterin...This paper proposes a clustering technique that minimizes the need for subjective human intervention and is based on elements of rough set theory （RST）. The proposed algorithm is unified in its approach to clustering and makes use of both local and global data properties to obtain clustering solutions. It handles single-type and mixed attribute data sets with ease. The results from three data sets of single and mixed attribute types are used to illustrate the technique and establish its efficiency.展开更多
In this paper, we applied the rough sets to the point cluster and river network selection. In order to meet the requirements of rough sets, first, we structuralize and quantify the spatial information of objects by co...In this paper, we applied the rough sets to the point cluster and river network selection. In order to meet the requirements of rough sets, first, we structuralize and quantify the spatial information of objects by convex hull, triangulated irregular network (TIN), Voronoi diagram, etc.;second, we manually assign decisional attributes to the information table according to conditional attributes. In doing so, the spatial information and attribute information are integrated together to evaluate the importance of points and rivers by rough sets theory. Finally, we select the point cluster and the river network in a progressive manner. The experimental results show that our method is valid and effective. In comparison with previous work, our method has the advantage to adaptively consider the spatial and attribute information at the same time without any a priori knowledge.展开更多
本研究采用文献计量学方法,总结当前土壤质量研究中最小数据集(MDS)选取的方法和指标,定量分析并指出土壤质量评价中最小数据集的热点和前沿,为中国土壤质量评价和农业绿色发展提供科学参考。通过检索1991-2022年CNKI和Web of Science...本研究采用文献计量学方法,总结当前土壤质量研究中最小数据集(MDS)选取的方法和指标,定量分析并指出土壤质量评价中最小数据集的热点和前沿,为中国土壤质量评价和农业绿色发展提供科学参考。通过检索1991-2022年CNKI和Web of Science相关文献,收集了文献中310个最小数据集进行筛选,借助CiteSpace和VOSviewer对年度发文量、国家/地区、机构、期刊进行共现分析,对关键词进行突现词和聚类分析。31年来该领域文献量逐步增加并仍处于快速发展阶段,中国是发文量最多的国家,期刊载文量最多的为《土壤通报》《生态学报》和Ecological Indicators;主要研究热点表现在“农业管理对土壤质量影响、土壤退化与修复、土壤质量对气候变化的响应与应对及最小数据集筛选方法与模型构建”等方面;前期MDS在土壤质量评价中选用较多的主要为物理、化学指标,但随着土壤健康的发展,生物学指标逐步增长。在未来一段时间内MDS发文量仍为快速增长阶段,发展中国家在全球起着重要节点作用;MDS核心指标为土壤有机质/碳(SOM/SOC)、pH、全氮、速效磷和容重;未来研究应注重在基于大数据平台构建不同尺度下静态评价与动态监测相结合的综合反映土壤功能的土壤健康质量评价框架体系,探讨气候变化背景下与土壤质量变化相对应的MDS及其指标体系,构建精准反映土壤质量变化规律的评价模型与最优最小数据集。展开更多
基金Supported by National Natural Science Foundation of China(60675039)National High Technology Research and Development Program of China(863 Program)(2006AA04Z217)Hundred Talents Program of Chinese Academy of Sciences
文摘This paper presents a fully automatic segmentation method of liver CT scans using fuzzy c-mean clustering and level set. First, the contrast of original image is enhanced to make boundaries clearer;second, a spatial fuzzy c-mean clustering combining with anatomical prior knowledge is employed to extract liver region automatically;thirdly, a distance regularized level set is used for refinement;finally, morphological operations are used as post-processing. The experiment result shows that the method can achieve high accuracy (0.9986) and specificity (0.9989). Comparing with standard level set method, our method is more effective in dealing with over-segmentation problem.
文摘This paper proposes a clustering technique that minimizes the need for subjective human intervention and is based on elements of rough set theory （RST）. The proposed algorithm is unified in its approach to clustering and makes use of both local and global data properties to obtain clustering solutions. It handles single-type and mixed attribute data sets with ease. The results from three data sets of single and mixed attribute types are used to illustrate the technique and establish its efficiency.
文摘In this paper, we applied the rough sets to the point cluster and river network selection. In order to meet the requirements of rough sets, first, we structuralize and quantify the spatial information of objects by convex hull, triangulated irregular network (TIN), Voronoi diagram, etc.;second, we manually assign decisional attributes to the information table according to conditional attributes. In doing so, the spatial information and attribute information are integrated together to evaluate the importance of points and rivers by rough sets theory. Finally, we select the point cluster and the river network in a progressive manner. The experimental results show that our method is valid and effective. In comparison with previous work, our method has the advantage to adaptively consider the spatial and attribute information at the same time without any a priori knowledge.
文摘本研究采用文献计量学方法,总结当前土壤质量研究中最小数据集(MDS)选取的方法和指标,定量分析并指出土壤质量评价中最小数据集的热点和前沿,为中国土壤质量评价和农业绿色发展提供科学参考。通过检索1991-2022年CNKI和Web of Science相关文献,收集了文献中310个最小数据集进行筛选,借助CiteSpace和VOSviewer对年度发文量、国家/地区、机构、期刊进行共现分析,对关键词进行突现词和聚类分析。31年来该领域文献量逐步增加并仍处于快速发展阶段,中国是发文量最多的国家,期刊载文量最多的为《土壤通报》《生态学报》和Ecological Indicators;主要研究热点表现在“农业管理对土壤质量影响、土壤退化与修复、土壤质量对气候变化的响应与应对及最小数据集筛选方法与模型构建”等方面;前期MDS在土壤质量评价中选用较多的主要为物理、化学指标,但随着土壤健康的发展,生物学指标逐步增长。在未来一段时间内MDS发文量仍为快速增长阶段,发展中国家在全球起着重要节点作用;MDS核心指标为土壤有机质/碳(SOM/SOC)、pH、全氮、速效磷和容重;未来研究应注重在基于大数据平台构建不同尺度下静态评价与动态监测相结合的综合反映土壤功能的土壤健康质量评价框架体系,探讨气候变化背景下与土壤质量变化相对应的MDS及其指标体系,构建精准反映土壤质量变化规律的评价模型与最优最小数据集。
