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Modeling Multi-object Configurations via Medial/Skeletal Linking Structures

机译:通过内侧/骨架连接结构建模多对象配置

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We introduce a method for modeling a configuration of objects in 2D or 3D images using a mathematical "skeletal linking structure" which will simultaneously capture the individual shape features of the objects and their positional information relative to one another. The objects may either have smooth boundaries and be disjoint from the others or share common portions of their boundaries with other objects in a piecewise smooth manner. These structures include a special class of "Blum medial linking structures", which are intrinsically associated to the configuration and build upon the Blum medial axes of the individual objects. We give a classification of the properties of Blum linking structures for generic configurations. The skeletal linking structures add increased flexibility for modeling configurations of objects by relaxing the Blum conditions and they extend in a minimal way the individual "skeletal structures" which have been previously used for modeling individual objects and capturing their geometric properties. This allows for the mathematical methods introduced for single objects to be significantly extended to the entire configuration of objects. These methods not only capture the internal shape structures of the individual objects but also the external structure of the neighboring regions of the objects. In the subsequent second paper (Damon and Gasparovic in Shape and positional geometry of multi-object configurations) we use these structures to identify specific external regions which capture positional information about neighboring objects, and we develop numerical measures for closeness of portions of objects and their significance for the configuration. This allows us to use the same mathematical structures to simultaneously analyze both the shape properties of the individual objects and positional properties of the configuration. This provides a framework for analyzing the statistical properties of collections of similar configurations such as for applications to medical imaging.
机译:我们介绍一种使用数学“骨架连接结构”在2D或3D图像中建模对象的配置的方法,该数学“骨架连接结构”将同时捕获对象的各个形状特征及其位置信息相对于彼此。对象可以具有平滑的边界,并且与其他对象与其他对象分享其边界的公共部分以逐分平滑的方式。这些结构包括特殊类别的“BLUM内侧连接结构”,其与构造有本质上与各个物体的布鲁姆内侧轴线相关联。我们为通用配置提供了BLUM连接结构的属性的分类。骨架连接结构增加了通过放松Blum条件来建模物体的配置,并且它们以先前用于建模单个物体和捕获其几何特性的单个“骨架结构”以最小的方式延伸。这允许为单个对象引入的数学方法,以显着扩展到对象的整个配置。这些方法不仅捕获各个物体的内部形状结构,而且仅捕获对象的相邻区域的外部结构。在随后的第二纸(Damon和Modeal Concumurations的形状和位置几何形状中的Damon和GaspAcovic)中,我们使用这些结构来识别捕获关于相邻对象的位置信息的特定外部区域,并且我们开发了对物体部分的近距离的数值措施及其配置的重要性。这允许我们使用相同的数学结构来同时分析各个对象的形状属性和配置的位置属性。这提供了一种用于分析类似配置的统计特性的框架,例如用于医学成像的应用。

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