CRII: ACI: 4D Dynamic Anisotropic Meshing and Applications

在医疗保健、交通运输和仿真领域，需要实时地从复杂的场景中真实地重建、可视化和捕获时空（4D）模型/图像（动态对象）。例如，高保真动态建模和实时可视化器官及其周围组织的4D变形形状和变化对于建立有效的4D模型规划/捕获放射治疗（例如，4D- doctor系统）非常重要。它需要动态各向异性建模和多模态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，用于高效地计算具有大规模体图像数据中特征和细节的复杂四维物体的高质量动态各向异性网格模型。该项目涉及多个学科，如几何建模、计算机图形学和医学图像处理，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本科和研究生阶段的计算机科学与工程课程。因此，这项研究与美国国家科学基金会促进科学进步和促进国家健康、繁荣和福利的使命是一致的。一个高质量和高效率的四维动态各向异性网格的理论和计算框架对于解决ef&amp；#64257；科学地表示和捕获4D数据。该项目的关键优势集中在基于粒子的黎曼度量网格建模方法的变革性研究思想和方法，作为几何引导的3D/4D成像信息学的基础。提出的探索性研究活动将解决以下主要主题和目标：(1)开发一种基于粒子的高质量3D和4D各向异性四面体网格划分的新方法；(2)评估网格质量并将提出的理论网格划分方法应用于医学成像，并开发了一个测试平台系统，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。统一的基于粒子的理论网格框架，将高斯能量、动态黎曼度量和高维嵌入理论相结合，可以从全新的角度高效生成动态各向异性网格。这项研究计划是创新的，因为它将建立一个新的几何建模框架，支持3D/4D成像信息学。

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.