LMap: Shape-Preserving Local Mappings for Biomedical Visualization.
LMap: Shape-Preserving Local Mappings for Biomedical Visualization.
复制标题
LMap：用于生物医学可视化的形状保持局部映射。
DOI：
10.1109/tvcg.2017.2772237
复制
发表时间：
2018
影响因子：
5.2
通讯作者：
Kaufman,ArieE
中科院分区：
文献类型：
--
作者：
Nadeem,Saad;Gu,Xianfeng;Kaufman,ArieE
医学器官和生物结构的可视化是一项具有挑战性的任务，因为它们的复杂几何形状和由此产生的闭塞。全局球面和平面映射技术简化了复杂的几何形状，并解决了遮挡问题，以帮助可视化。然而，虽然解决这些技术的闭塞不保留的几何背景下，使他们不太适合关键任务的生物医学可视化任务。在本文中，我们提出了一个形状保持局部映射技术解决闭塞，同时保持整体的几何背景。更具体地说，我们提出了一种新的可视化算法，LMap，保形参数化和变形的任意表面上选定的局部区域的兴趣（ROI）。所得到的形状保持局部映射有助于可视化复杂的表面，同时保持整体的几何背景。该算法是基于鲁棒性和高效的外部Ricci流技术，并使用动态Ricci流算法，以保证存在一个局部地图的任意表面上的一个选定的ROI。我们在三个具有挑战性的用例中展示了我们的方法的有效性和功效：（1）多模态大脑可视化，（2）虚拟结肠镜中心线飞行的最佳覆盖范围，以及（3）分子表面可视化。
Visualization of medical organs and biological structures is a challenging task because of their complex geometry and the resultant occlusions. Global spherical and planar mapping techniques simplify the complex geometry and resolve the occlusions to aid in visualization. However, while resolving the occlusions these techniques do not preserve the geometric context, making them less suitable for mission-critical biomedical visualization tasks. In this paper, we present a shape-preserving local mapping technique for resolving occlusions locally while preserving the overall geometric context. More specifically, we present a novel visualization algorithm, LMap, for conformally parameterizing and deforming a selected local region-of-interest (ROI) on an arbitrary surface. The resultant shape-preserving local mappings help to visualize complex surfaces while preserving the overall geometric context. The algorithm is based on the robust and efficient extrinsic Ricci flow technique, and uses the dynamic Ricci flow algorithm to guarantee the existence of a local map for a selected ROI on an arbitrary surface. We show the effectiveness and efficacy of our method in three challenging use cases: (1) multimodal brain visualization, (2) optimal coverage of virtual colonoscopy centerline flythrough, and (3) molecular surface visualization.