Automatic Viewpoint Selection for Exploration of Time-Dependent Cerebral Aneurysm Data
Automatic Viewpoint Selection for Exploration of Time-Dependent Cerebral Aneurysm Data
复制标题
用于探索时间依赖性脑动脉瘤数据的自动视点选择
DOI：
10.1007/978-3-662-54345-0_79
复制
发表时间：
2017
影响因子：
2.5
通讯作者：
K. Lawonn
中科院分区：
文献类型：
--
作者：
M. Meuschke;W. Engelke;O. Beuing;B. Preim;K. Lawonn
本文提出了一种自动选择的观点，形成一个相机的路径，以支持探索脑动脉瘤。动脉瘤有破裂的风险，对患者造成致命后果。对于破裂风险评估，有必要结合形态学和血流动力学数据进行研究。然而，时间依赖性数据的广泛性质使分析复杂化。在探索过程中，领域专家必须手动确定适当的视图，这可能是一个繁琐而耗时的过程。我们的方法根据壁厚或压力等输入数据自动确定最佳视点。视点选择被建模为一个优化问题。我们的技术被应用到五个数据集，我们评估结果与两个领域的专家进行非正式访谈。
This paper presents an automatic selection of viewpoints, forming a camera path, to support the exploration of cerebral aneurysms. Aneurysms bear the risk of rupture with fatal consequences for the patient. For the rupture risk evaluation, a combined investigation of morphological and hemodynamic data is necessary. However, the extensive nature of the time-dependent data complicates the analysis. During exploration, domain experts have to manually determine appropriate views, which can be a tedious and time-consuming process. Our method determines optimal viewpoints automatically based on input data such as wall thickness or pressure. The viewpoint selection is modeled as an optimization problem. Our technique is applied to five data sets and we evaluate the results with two domain experts by conducting informal interviews.