CRII: ACI: 4D Dynamic Anisotropic Meshing and Applications

在医疗、交通和仿真领域中，存在着实时地从复杂场景中逼真地重建、可视化和捕捉时空(4D)模型/图像(动态对象)的需求。例如，实时地对器官及其周围组织的4D可变形形状和变化进行高保真的动态建模和可视化对于建立有效的用于放射治疗的4D模型规划/捕获变得重要(例如，4D-Doctor系统)。它需要动态各向异性建模和多通道成像技术来实现准确的配准、分割和可视化。本项目的目标是开发一种工具，用于高效地计算大规模体图像数据中具有特征和细节的复杂4D对象的高质量4D动态各向异性网格划分模型。该项目涉及几何建模、计算机图形学和医学图像处理等多个学科，有可能为跨学科研究和教育整合提供一个高质量的平台。该项目旨在丰富韦恩州立大学的计算机科学和工程课程，包括本科生和研究生。因此，这项研究符合美国国家科学基金会的使命，即促进科学进步，促进国民健康、繁荣和福祉。高质量和高效率的4D动态各向异性网格划分的理论和计算框架对于应对当前表示和捕获4D数据的挑战至关重要。该项目的主要优势集中在基于粒子的黎曼公制网格建模方法中的变革性研究思路和方法，作为几何制导的3D/4D成像信息学的基础。这些探索性的研究活动将针对以下主要主题和目标：(1)开发一种新的基于粒子的高质量3D和4D各向异性四面体网格划分方法；(2)评估网格划分质量并将所提出的理论网格划分方法应用于医学成像，并开发一个测试平台系统以评估其在4D-Doctor系统中的能力和潜力，包括4D图像配准和分割。统一的基于粒子的网格划分框架，集成了高斯能量、动态黎曼度量和高维嵌入理论，可以从一个全新的角度高效地生成动态各向异性网格。这项研究具有创新性，因为它将建立一个支持3D/4D成像信息学的新的几何建模框架。

There is an emerging need in healthcare, transportation, and simulation areas to realistically reconstruct, visualize, and capture space-time (4D) models/images (dynamic objects) from a complicated scenario in real-time. For example, high-fidelity dynamically modeling and visualizing 4D deformable shapes and variations of organs and their surrounding tissues in real-time become important for building an effective 4D model planning/capturing for radiation therapy (e.g., 4D-Doctor system). It requires dynamic anisotropic modeling and multi-modality imaging techniques for accurate registration, segmentation, and visualization. The goal of this project is to develop a tool for efficiently computing high-quality 4D dynamic anisotropic meshing models for complicated 4D objects with features and details in the large-scale volume image data. This project involves several disciplines, such as geometric modeling, computer graphics, and medical image processing, and has a potential to provide a high-quality platform for both interdisciplinary research and education integration. This project will aim to enrich the computer science and engineering curriculum at Wayne State University in both the undergraduate and graduate levels. Therefore, this research aligns with the NSF mission to promote the progress of science and to advance the national health, prosperity and welfare.A theoretical and computational framework for 4D dynamic anisotropic meshing with high quality and efficiency is essential for tackling challenges in efficiently representing and capturing the 4D data. The key strength of this project focuses on the transformative research ideas and approaches in particle-based approach for Riemannian metric mesh modeling, serving as a foundation for geometry-guided 3D/4D imaging informatics. The proposed exploratory research activities will address the following major themes and objectives: (1) to develop a novel particle-based method for high-quality 3D and 4D anisotropic tetrahedral meshing; (2) to evaluate the mesh quality and apply the proposed theoretical meshing approaches in applications to medical imaging, and develop a testbed system to evaluate its capability and potential in 4D-Doctor system, including 4D image registration and segmentation. The unified theoretical particle-based meshing framework, integrating Gaussian energy, dynamic Riemannian metrics, and high-dimensional embedding theory, can enable efficient generation of dynamic anisotropic meshes from a brand new perspective. This research initiative is innovative as it will establish a novel geometric modeling framework supporting 3D/4D imaging informatics.