Webster Roger, Harris Matt, Shenk Rod, Blumenstock John, Gerber Jesse, Billman Chad, Benson Aaron, Haluck Randy
Department of Computer Science, Caputo Hall, Millersville University, Millersville, PA 17551, USA.
Stud Health Technol Inform. 2005;111:596-8.
This paper describes a technique for efficient collision detection and deformation of abdominal organs in surgical simulation using an approximation of the Euclidean skeleton. Many researchers have developed surgical simulators, but one of the most difficult underlying problems is that of organ-instrument collision detection followed by the deformation of the tissue caused by the instrument. Much of the difficulty is due to the vast number of polygons in high resolution complex organ models. A high resolution gall bladder model for instance can number in the tens of thousands of polygons. Our methodology utilizes the reduction power of the skeleton to reduce computations. First, we recursively compute approximations to the Euclidean skeleton to generate a set of skeletal points for the organ. Then we pre-compute for each vertex in each polygon the associated skeleton point (minimal distance discs). A spring is then connected from each vertex to its associated skeleton point to be used in the deformation algorithm. The data structure for the organ thus stores for each skeletal point its maximum and minimum distances and the list of associated vertices. A heuristic algorithm using the skeleton structure of the instrument and the skeleton of the organ is used to determine instrument collisions with the organ.
本文描述了一种在手术模拟中使用欧几里得骨架近似来实现腹部器官高效碰撞检测和变形的技术。许多研究人员已经开发了手术模拟器，但最困难的潜在问题之一是器官与器械的碰撞检测以及器械导致的组织变形。大部分困难源于高分辨率复杂器官模型中大量的多边形。例如，一个高分辨率胆囊模型的多边形数量可能数以万计。我们的方法利用骨架的简化能力来减少计算量。首先，我们递归计算欧几里得骨架的近似值，以生成器官的一组骨架点。然后，我们为每个多边形中的每个顶点预先计算相关的骨架点（最小距离圆盘）。接着，从每个顶点连接一个弹簧到其相关的骨架点，以便在变形算法中使用。器官的数据结构因此为每个骨架点存储其最大和最小距离以及相关顶点的列表。一种使用器械骨架结构和器官骨架的启发式算法用于确定器械与器官的碰撞。
