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System for Integrated Neuroimaging Analysis and Processing of Structure

机译:用于集成神经影像分析分析和结构的系统

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摘要

Mapping brain structure in relation to neurological development, function, plasticity, and disease is widely considered to be one of the most essential challenges for opening new lines of neuro-scientific inquiry. Recent developments with MRI analysis of structural connectivity, anatomical brain segmentation, cortical surface parcellation, and functional imaging have yielded fantastic advances in our ability to probe the neurological structure-function relationship in vivo. To date, the image analysis efforts in each of these areas have typically focused on a single modality. Here, we extend the cortical reconstruction using implicit surface evolution (CRUISE) methodology to perform efficient, consistent, and topologically correct analyses in a natively multi-parametric manner. This effort combines and extends state-of-the-art techniques to simultaneously consider and analyze structural and diffusion information alongside quantitative and functional imaging data. Robust and consistent estimates of the cortical surface extraction, cortical labeling, diffusion-inferred contrasts, diffusion tractography, and subcortical parcellation are demonstrated in a scan-rescan paradigm. Accompanying this demonstration, we present a fully automated software system complete with validation data.
机译:映射与神经发育,功能,可塑性和疾病相关的大脑结构被广泛认为是开辟新的神经科学探究途径的最重要挑战之一。 MRI在结构连接性,解剖学上的脑部分割,皮层表面分裂和功能成像方面的最新进展,使我们在体内探测神经结构与功能之间关系的能力取得了惊人的进步。迄今为止,在这些领域中的每一个领域中的图像分析工作通常都集中在一种模式上。在这里,我们使用隐式表面演化(CRUISE)方法扩展了皮质重建,以本机多参数方式执行高效,一致且拓扑正确的分析。这项工作结合并扩展了最先进的技术,可同时考虑和分析结构和扩散信息以及定量和功能成像数据。在扫描-再扫描范例中证明了对皮层表面提取,皮层标记,扩散推断的对比,弥散束摄影和皮层下剥离的鲁棒且一致的估计。伴随此演示,我们展示了一个完整的带有验证数据的全自动软件系统。

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