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.

在科学和工程发现中，有效地获取和处理复杂的微观结构及其形态变得越来越重要。动物和人类研究中越来越多的证据表明，微脑血管异常是许多神经系统疾病和血管疾病的真正来源。因此，迫切需要更好地检测和理解微观水平的体内血管特征。但是，现有的技术和软件解决方案是基于用于处理宏观器官和组织的一般规模医学图像开发的，不适用于具有挑战性的下一代血管成像数据和微级别的脉管系统。此外，很难为域开发人员的特定科学微血管成像应用定制。该项目的总体目的是设计和开发一个严格，可扩展，智能，全面的数据和软件基础架构，微型摩擦处理器（MVP），该处理器（MVP）支持并维持理解和维持的进步，在理解和分析复杂的3D微血管网络上，为大型社区提供了多种多样的跨性别域名，并促进了持续的数据。微血管发现 - 通过高级软件网络基础结构以及用用驱动的功能应用和评估来生成新的知识，理解，并加速发现和创新。新开发的基于AI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集成在MVP系统中，作为软件基础架构中的核心模块。 MVP数据库包括许多具有不同解剖形状，形态学特征和不同数据模式的受试者，并作为基础架构（即知识基础）收集并构造，该基础结构提供了3D微血管网络跟踪和分析的知识。 MVP系统是根据开源和拖放实时应用系统设计和构建的，以降低人类劳动和计算成本，加速重新开发和可扩展性的速度和效率。这个独特的框架支持生物医学工程，大数据神经科学和基于AI的临床诊断的微脉管系统分析的广泛采用。高级Cyber​​infrasture办公室的奖项由工程局内化学，生物工程，环境和运输系统部共同支持。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响审查标准通过评估来获得支持的。