IMPROVEMENTS IN DIFFUSION TENSOR IMAGING (DTI)

扩散张量成像 (DTI) 的改进

• 批准号: 7955350
• 负责人: Michael E Moseley
• 金额: $ 2.41万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-06-01 至 2010-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7955350
• 关键词: Algorithms; Brain; Brain region; Cognitive; Computer Retrieval of Information on Scientific Projects Database; Computer software; Diffusion Magnetic Resonance Imaging; Fiber; Funding; Grant; Institution; Maps; Methods; Modeling; Motor; Pathway interactions; Pattern; Plants; Process; Protocols documentation; Reproducibility; Research; Research Personnel; Resources; Seeds; Source; Techniques; Technology; Time; United States National Institutes of Health; Writing; image reconstruction; trafficking; vector; white matter

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The overall aim of this project is to map the potential pathways of cognitive and motor activation. This has progressed in the last year to add several improvements in the DTI image reconstruction and processing software (?Tensorcalc?) that we wrote and maintain for the P41 RR09784. Diffusion tensor imaging (DTI) is a promising new technique for the assessment of white matter (WM) structural integrity and connectivity. We have written and refined 3 key core DTI map tracking algorithms that are being used to track white matter fibers for determining the potential white matter trafficking patterns. One of the more exciting methods to arise from the noninvasive mapping of white matter tracks is the potential of tracking the white matter fibers from one region of brain to another. This in essence, reveals the underlying ?wiring? of the activated brain. Our algorithm allows for real-time connectivity maps that can be generated from planting a seed in one white matter tract region. We have constructed software ?phantoms? to check the algorithms for accuracy and reproducibility. Our diffusion tensor imaging protocol is performed using a spin echo EPI technique and we have added a host of new spiral methods. The vector maps hold the orientation of the fibers as well as the magnitude of the orientation. From the fiber maps, one can compose several general approaches to finding connectivity from fiber to fiber from a variety of model algorithms that we have built.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 该项目的总体目的是绘制认知和运动激活的潜在途径。在去年的发展中，这已经取得了进展，以在我们为P41 RR09784编写和维护的DTI图像重建和处理软件（？Tensorcalc？）中增加了一些改进。扩散张量成像（DTI）是评估白质（WM）结构完整性和连通性的有希望的新技术。我们已经编写并完善了3个关键的核心DTI地图跟踪算法，这些算法用于跟踪白质纤维以确定潜在的白质运输模式。白质轨迹的无创映射引起的更令人兴奋的方法之一是潜在的潜力是跟踪从一个大脑的一个区域到另一个区域的白质纤维。从本质上讲，这揭示了基础？接线？激活的大脑。我们的算法允许通过在一个白质区域种植种子生成的实时连通图。我们已经构建了软件？幻影？检查算法的准确性和可重复性。我们的扩散张量成像协议是使用自旋回波EPI技术执行的，我们添加了许多新的螺旋方法。矢量图保持纤维的方向以及方向的大小。从光纤地图中，可以从我们构建的各种模型算法中找到从纤维到纤维的连接性的几种通用方法。