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基于双距离场的三维中心路径提取算法

A 3-D Center Path Finding Algorithm Base on Two Distance Fields

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【作者】 胡英侯悦徐心和

【Author】 HU Ying, HOU Yue, XU Xin-he (Institute of AI and Robotics, Northeastern University, Shenyang 110004) (Shenyang Neusoft Digital Medical Systems Co. ,Ltd, Shenyang 110179)

【机构】 东北大学人工智能与机器人研究所沈阳东软数字医疗系统股份有限公司东北大学人工智能与机器人研究所 沈阳 110004 沈阳东软数字医疗系统股份有限公司沈阳 110179沈阳 110004

【摘要】 在真实的三维数据场中,自动地提取中心路径是实现自动漫游的关键问题.为了解决当前中心路径自动 提取算法中存在的效果差,计算量大的问题,提出了一种基于双距离场的快速三维中心路径提取算法,该算法对于 任意给定可连通的起点和终点,首先建立基于起点的源距离场和基于边界的边界距离场,然后通过两个距离场的 共同约束来快速地提取出一条连接起点和终点的中心路径,同时为了保证漫游的效果,还采用3次B样条曲线对 所获取的路径进行了光滑,最后在PC机平台上实现和测试了该算法,实验结果证明,该算法不仅速度快、效果好, 而且具有很高的灵活性.

【Abstract】 Automatic center-path finding in real 3-D data set is the key problem in realization of automatic navigation. Many methods have been proposed, but most of them are either quality depressed or time expensive. In this paper, after summarize the main existent methods, a new 3D center path finding algorithm base on two distance fields is proposed: Between any given start-point and end-point which can be connected, the source distance field base on the start-point and the boundary distance field base on the boundary are established. Through the co-restriction of the two-distance field, a center path that connects the start-point and end-pint can be found. In order to enhance the effect of navigation, a cubic B-spline curve is used to smooth the path. The algorithm is realized on PC platform and two medicine image date sets are used for test. Computer time and path finding results are shown in Section 4. As compared with onion peeling algorithm and Dijkstra’s Single Source Shortest Path Algorithm, the result shows that the algorithm not only can get fast speed and high quality result, but also has more flexibility. The application in Virtual endoscopy is also shown in the end of the paper.

【关键词】 三维中心路径距离场自动漫游
【Key words】 3D center pathDist fieldAutomatic navigation
  • 【文献出处】 中国图象图形学报 ,Journal of Image and Graphics , 编辑部邮箱 ,2003年11期
  • 【分类号】TP391.41
  • 【被引频次】40
  • 【下载频次】293
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