IMPROVEMENTS IN DIFFUSION TENSOR IMAGING (DTI)

扩散张量成像 (DTI) 的改进

• 批准号: 7601870
• 负责人: Michael E Moseley
• 金额: $ 2.88万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-06-01 至 2008-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7601870
• 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; 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.

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 这个项目的总体目标是绘制认知和运动激活的潜在路径图。这在去年取得了进展，在DTI图像重建和处理软件(Tensorcalc)中增加了几项改进。我们为P41 RR09784编写和维护的。弥散张量成像(DTI)是一种很有前途的新技术，可用于评估脑白质结构的完整性和连接性。我们编写并改进了3个关键的核心DTI地图跟踪算法，用于跟踪白质纤维，以确定潜在的白质运输模式。从脑白质轨迹的非侵入性映射中产生的更令人兴奋的方法之一是追踪从大脑的一个区域到另一个区域的白质纤维的可能性。本质上，这揭示了潜在的？布线？被激活的大脑。我们的算法允许实时连接地图，可以通过在一个白质束区域种植种子来生成。我们已经构建了软件？幻影？检查算法的准确性和重复性。我们的扩散张量成像协议是使用自旋回波EPI技术执行的，我们增加了一系列新的螺旋方法。矢量贴图保存纤维的方向以及方向的大小。从光纤图中，我们可以根据我们构建的各种模型算法组成几种通用方法来查找光纤到光纤的连通性。