The growing complexity of spatial and structural information in 3D data makes data inspection and visualization a challenging task. We describe a method to create a planar embedding of 3D treelike structures using their skeleton representations. Our method maintains the original geometry, without overlaps, to the best extent possible, allowing exploration of the topology within a single view. We present a novel camera view generation method which maximizes the visible geometric attributes (segment shape and relative placement between segments). Camera views are created for individual segments and are used to determine local bending angles at each node by projecting them to 2D. The final embedding is generated by minimizing an energy function (the weights of which are user adjustable) based on branch length and the 2D angles, while avoiding intersections. The user can also interactively modify segment placement within the 2D embedding, and the overall embedding will update accordingly. A global to local interactive exploration is provided using hierarchical camera views that are created for subtrees within the structure. We evaluate our method both qualitatively and quantitatively and demonstrate our results by constructing planar visualizations of line data (traced neurons) and volume data (CT vascular and bronchial data
翻译:3D 数据中空间和结构信息日益复杂的空间和结构信息日益复杂,使得数据检查和可视化成为一项具有挑战性的任务。我们描述一种方法,用它们的骨骼表示来建立3D树形结构的平面嵌入图层。我们的方法尽可能保持原始几何,不重叠,允许在单一的视图中进行地形学的探索。我们展示了一种新型相机生成方法,使可见的几何属性最大化(区块形状和区块之间的相对位置)。为单个区段创建了相机视图,并用来通过投射到 2D 来确定每个节点的本地弯角。最后嵌入的方法是最大限度地减少基于分支长度和2D 角度的能量函数(其重量可以调整的用户重量),同时避免交叉。用户还可以交互修改2D 嵌入内的区段位置,总体嵌入将相应更新。一个全球到地方的交互式探索是使用为结构中的子树木创建的分级相机视图提供的。我们从质量和数量上评价了我们的方法,并通过建造直观线数据(色神经和气轴)和体数据量量表显示我们的结果。