CAREER: Spectral Deformable Models: Theory and Applications

职业：谱变形模型：理论与应用

• 批准号: 1149737
• 负责人: Xiaohu Guo
• 金额: $ 43.24万
• 依托单位: University of Texas at Dallas
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1149737&HistoricalAwards=false
• 关键词: CAREER; Spectral; Deformable; Models; Theory

With the popularity of real-time 3D/4D data capturing capabilities, there is an emerging need to compute the deformable models over the networks. Traditional model-driven deformable models have their bottlenecks since the spatial information for large-scale datasets cannot be efficiently solved and adaptively minimized over different network conditions. This project centers on the concept of spectrum-driven deformable models. Analogous to Fourier analysis being applied to image processing, the spectral deformable models employ manifold harmonics to efficiently and effectively perform segmentation, registration, physics-based simulation, compression, and streaming of 3D deformable surfaces and volumes.In this project, manifold harmonics are used to transform arbitrary scanned datasets into a reduced diffusion subspace, in which real-time segmentation, registration, and physics-based simulation can be performed. Besides the stretching deformations, the rotational and tensor fields are encoded with manifold harmonics, which provides a "spectral multiresolution" structure to compress and stream deformable models over different network conditions.The PI works with the medical imaging experts at UT Southwestern Medical Center, to build a tele-diagnosis system for evaluating each component in the spectral deformable models. The test-bed on tele-medicine has impacts on the next-generation diagnosis and treatment services, as well as on clinical education. The theoretical and technical breakthrough can benefit our society at large, from tele-immersion, remote sensing, to speech training, through the PI?s further outreach activities. The research and education are integrated by taking research advances into existing and future courses; developing the visualization software for education; and attracting more undergraduate students into research.

随着实时 3D/4D 数据捕获功能的普及，通过网络计算可变形模型的需求不断涌现。传统的模型驱动的可变形模型存在瓶颈，因为大规模数据集的空间信息无法在不同的网络条件下有效求解和自适应最小化。该项目以谱驱动变形模型的概念为中心。类似于应用于图像处理的傅立叶分析，光谱可变形模型采用流形谐波来高效且有效地执行 3D 可变形表面和体积的分割、配准、基于物理的模拟、压缩和流式传输。在该项目中，使用了流形谐波将任意扫描数据集转换为简化的扩散子空间，在其中可以执行实时分割、配准和基于物理的模拟。除了拉伸变形之外，旋转场和张量场还用流形谐波进行编码，这提供了“光谱多分辨率”结构，可以在不同的网络条件下压缩和流式传输可变形模型。PI 与 UT 西南医学中心的医学成像专家合作，建立一个远程诊断系统来评估光谱变形模型中的每个组件。远程医疗试验台对下一代诊断和治疗服务以及临床教育产生影响。通过 PI 的进一步推广活动，理论和技术突破可以使我们整个社会受益，从远程沉浸、遥感到语音训练。通过将研究进展融入现有和未来的课程中，将研究和教育融为一体；开发教育可视化软件；吸引更多本科生参与研究。