Department of Electrical Engineering, Vanderbilt University, Nashville, TN 37235-1679, USA.
Neuroinformatics. 2013 Jan;11(1):91-103. doi: 10.1007/s12021-012-9159-9.
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.
将大脑结构与神经发育、功能、可塑性和疾病相关联的研究被广泛认为是开启神经科学新研究方向的最关键挑战之一。最近，磁共振成像（MRI）分析结构连接、解剖脑分割、皮质表面分区和功能成像方面的发展，使我们在活体探测神经结构-功能关系的能力上取得了巨大的进步。迄今为止，这些领域中的图像分析工作通常都集中在单一模式上。在这里，我们将使用隐式曲面演化（CRUISE）方法扩展皮质重建（cortical reconstruction using implicit surface evolution，CRUISE）方法，以原生多参数方式进行高效、一致且拓扑正确的分析。这一努力结合并扩展了最先进的技术，以便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-重扫范例中，对皮质提取、皮质标记、扩散推断对比、扩散轨迹和皮质下分区的稳健和一致的估计进行了演示。伴随着这一演示，我们还展示了一个带有验证数据的全自动软件系统。
