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    • 71. 发明申请
    • PLACEMENT OF VIRTUAL MACHINES BASED ON SERVER COST AND NETWORK COST
    • 基于服务器成本和网络成本的虚拟机配置
    • US20110225277A1
    • 2011-09-15
    • US12721995
    • 2010-03-11
    • DOUGLAS M. FREIMUTHXiaoqiao MengVasileios PappasLi Zhang
    • DOUGLAS M. FREIMUTHXiaoqiao MengVasileios PappasLi Zhang
    • G06F9/455G06F15/173
    • G06F9/45558G06F2009/4557
    • A method, information processing system, and computer program product manage server placement of virtual machines in an operating environment. A mapping of each virtual machine in a plurality of virtual machines to at least one server in a set of servers is determined. The mapping substantially satisfies a set of primary constraints associated with the set of servers. A plurality of virtual machine clusters is created. Each virtual machine cluster includes a set of virtual machines from the plurality of virtual machines. A server placement of one virtual machine in a cluster is interchangeable with a server placement of another virtual machine in the same cluster while satisfying the set of primary constraints. A server placement of the set of virtual machines within each virtual machine on at least one mapped server is generated for each cluster. The server placement substantially satisfies a set of secondary constraints.
    • 一种方法,信息处理系统和计算机程序产品在操作环境中管理虚拟机的服务器放置。 确定多个虚拟机中的每个虚拟机到一组服务器中的至少一个服务器的映射。 该映射基本上满足与该组服务器相关联的一组主要约束。 创建多个虚拟机集群。 每个虚拟机集群包括来自多个虚拟机的一组虚拟机。 集群中的一个虚拟机的服务器放置可以与同一个集群中的另一个虚拟机的服务器位置互换,同时满足一组主要约束。 为每个集群生成至少一个映射服务器上的每个虚拟机内的虚拟机集合的服务器放置。 服务器放置基本上满足一组辅助约束。
    • 75. 发明授权
    • System and method for corpus callosum segmentation in magnetic resonance images
    • 磁共振图像中胼for体分割的系统和方法
    • US07983464B2
    • 2011-07-19
    • US11782828
    • 2007-07-25
    • Qing XuHong ChenLi Zhang
    • Qing XuHong ChenLi Zhang
    • G06K9/00
    • G06K9/6209G06K9/6207G06T7/0012G06T7/12G06T7/149G06T2207/10088G06T2207/20124G06T2207/30016
    • A method and system for segmentation of the corpus callosum in MR brain images is disclosed. The method utilizes an active shape model (ASM) with confidence weighting to iteratively adjust an initial corpus callosum contour to define a boundary of the corpus callosum in an MR image. An ASM is used to determine a displacement value in a perpendicular direction of the corpus callosum contour for each node of the corpus callosum contour. The displacement value for each node is then weighted based on a confidence of that displacement value. The ASM is then fitted to the adjusted contour. These steps are iteratively performed until the contour converges to define the corpus callosum boundary. This boundary can be further refined based on intensity distributions in object and background regions defined by the boundary.
    • 公开了MR脑图像中胼the体分割的方法和系统。 该方法利用具有置信度加权的活动形状模型(ASM)来迭代地调整初始语料库胼los体轮廓,以定义MR图像中胼the体的边界。 ASM用于确定胼the体轮廓的每个节点的胼um体轮廓的垂直方向上的位移值。 然后基于该位移值的置信度对每个节点的位移值加权。 然后将ASM安装到调整后的轮廓上。 迭代地执行这些步骤,直到轮廓收敛以定义胼the体边界。 该边界可以根据由边界定义的对象和背景区域中的强度分布进一步改进。