Elements: MVP: Open-Source AI-Powered MicroVessel Processor for Next-Generation Vascular Imaging Data

要素：MVP：用于下一代血管成像数据的开源人工智能微血管处理器

• 批准号: 2311245
• 负责人: Zichun Zhong
• 金额: $ 59.99万
• 依托单位: Wayne State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2311245&HistoricalAwards=false
• 关键词: Elements; MVP; Open; Source; AI

Effectively acquiring and processing complicated microstructures and their morphology become increasingly important in scientific and engineering discoveries. A growing body of evidence in animal and human studies shows that micro-cerebrovascular abnormalities are the real source of many neurologic disorders and vascular diseases. Therefore, there is an urgent need for better detection and understanding of vascular characteristics in vivo at the micro-level. However, the existing techniques and software solutions are developed based on general-scale medical images for processing macro-level organs and tissues, not applicable to the challenging next-generation vascular imaging data and micro-level vasculature. Furthermore, they are difficult to be customized to specific scientific microvascular imaging applications for domain developers. The overall objective of this project is to design and develop a rigorous, scalable, intelligent, and comprehensive data and software infrastructure, MicroVessel Processor (MVP), which supports and sustains advancements of understanding and analyzing the complicated 3D microvascular networks, provides services to a large community, and fosters continuous innovation in the multidisciplinary domains.This project integrates new paradigm of data-driven 3D microvascular discovery - generate new knowledge and understanding and accelerate discovery and innovation via the advanced software cyberinfrastructure, along with use-case driven functional applications and evaluations. The capabilities of the newly developed AI-based high-fidelity 3D image enhancement, 3D geometric segmentation / extraction, reconstruction, and analytics techniques are integrated in the MVP system as the core modules in the software infrastructure. The MVP database including a large number of subjects with varying anatomical shapes, morphological features, and different data modalities is collected and constructed as the infrastructure (i.e., knowledgebase), which provides the knowledge for 3D microvascular networks tracking and analysis. The MVP system is designed and built based on an open-source and drag-drop real-time application system, in order to reduce both human labors and computation costs, accelerate the speed and efficiency of re-development and extensibility. This unique framework supports a wide adoption in microvasculature analytics in biomedical engineering, big-data neuroscience, and AI-based clinical diagnosis. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Chemical, Bioengineering, Environmental and Transport Systems within the Engineering Directorate.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

有效地获取和处理复杂的微结构及其形态在科学和工程发现中变得越来越重要。越来越多的动物和人类研究证据表明，微脑血管异常是许多神经系统疾病和血管疾病的真实的根源。因此，迫切需要在微观水平上更好地检测和了解体内血管特性。然而，现有的技术和软件解决方案是基于通用尺度医学图像开发的，用于处理宏观水平的器官和组织，不适用于具有挑战性的下一代血管成像数据和微观水平的脉管系统。此外，它们很难被定制为特定的科学微血管成像应用领域的开发人员。该项目的总体目标是设计和开发一个严格的，可扩展的，智能的，全面的数据和软件基础设施，微血管处理器（MVP），支持和维持理解和分析复杂的3D微血管网络的进步，为大型社区提供服务，并促进多学科领域的持续创新。该项目整合了数据驱动的3D微血管发现的新范式-通过先进的软件网络基础设施，沿着用例驱动的功能应用程序和评估，产生新的知识和理解，加速发现和创新。新开发的基于人工智能的高保真3D图像增强、3D几何分割/提取、重建和分析技术的功能作为软件基础设施的核心模块集成在MVP系统中。MVP数据库包括大量具有不同解剖形状、形态特征和不同数据模态的受试者，其被收集并构建为基础设施（即，知识库），其提供用于3D微血管网络跟踪和分析的知识。MVP系统是基于一个开源的拖放式实时应用系统设计和构建的，旨在减少人工和计算成本，加快二次开发的速度和效率，提高可扩展性。这种独特的框架支持在生物医学工程、大数据神经科学和基于AI的临床诊断中广泛采用微血管分析。该奖项由高级网络基础设施办公室颁发，并得到工程理事会化学、生物工程、环境和运输系统部门的共同支持。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。