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.

中文翻译：

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LMap：用于生物医学可视化的保形局部映射。

医学器官和生物结构的可视化是一项艰巨的任务，因为它们具有复杂的几何形状以及由此产生的阻塞。全局球面和平面贴图技术简化了复杂的几何形状并解决了遮挡问题，从而有助于可视化。但是，在解决遮挡时，这些技术无法保留几何背景，从而使其不太适合执行关键任务的生物医学可视化任务。在本文中，我们提出了一种保留形状的局部映射技术，以在局部保留遮挡的同时保留整个几何上下文。更具体地说，我们提出了一种新颖的可视化算法LMap，用于在任意表面上共形参数化和变形所选局部感兴趣区域（ROI）。所得的形状保持局部映射有助于在保留整个几何上下文的同时可视化复杂曲面。该算法基于健壮且有效的外部Ricci流动技术，并使用动态Ricci流动算法来保证在任意表面上存在用于选定ROI的局部图。我们在三种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）多模式大脑可视化；（2）虚拟结肠镜检查中心线飞越的最佳覆盖范围；以及（3）分子表面可视化。