Université Pierre et Marie Curie-Paris 6, Centre de Recherche de l'Institut du Cerveau et de la MoelleÉpinière, UMR-S975 Paris, France.
IEEE Trans Med Imaging. 2011 Jun;30(6):1214-27. doi: 10.1109/TMI.2011.2108665. Epub 2011 Jan 28.
The alignment and normalization of individual brain structures is a prerequisite for group-level analyses of structural and functional neuroimaging data. The techniques currently available are either based on volume and/or surface attributes, with limited insight regarding the consistent alignment of anatomical landmarks across individuals. This article details a global, geometric approach that performs the alignment of the exhaustive sulcal imprints (cortical folding patterns) across individuals. This DIffeomorphic Sulcal-based COrtical (DISCO) technique proceeds to the automatic extraction, identification and simplification of sulcal features from T1-weighted Magnetic Resonance Image (MRI) series. These features are then used as control measures for fully-3-D diffeomorphic deformations. Quantitative and qualitative evaluations show that DISCO correctly aligns the sulcal folds and gray and white matter volumes across individuals. The comparison with a recent, iconic diffeomorphic approach (DARTEL) highlights how the absence of explicit cortical landmarks may lead to the misalignment of cortical sulci. We also feature DISCO in the automatic design of an empirical sulcal template from group data. We also demonstrate how DISCO can efficiently be combined with an image-based deformation (DARTEL) to further improve the consistency and accuracy of alignment performances. Finally, we illustrate how the optimized alignment of cortical folds across subjects improves sensitivity in the detection of functional activations in a group-level analysis of neuroimaging data.
个体脑结构的配准和归一化是进行结构和功能神经影像学数据组水平分析的前提。目前可用的技术要么基于体积和/或表面属性,要么对个体间解剖标志的一致配准只有有限的了解。本文详细介绍了一种全局、几何方法,用于在个体间对齐详尽的脑沟印痕(皮质折叠模式)。这种基于形态差异的脑沟皮质配准(DISCO)技术可以自动从 T1 加权磁共振成像(MRI)序列中提取、识别和简化脑沟特征。然后,这些特征被用作全 3-D 形态差异变形的控制措施。定量和定性评估表明,DISCO 可以正确地在个体间对齐脑沟褶皱和灰质和白质体积。与最近的标志性形态差异方法(DARTEL)的比较突出了缺乏显式皮质标志可能导致皮质脑沟的配准错误。我们还在组数据的自动设计经验性脑沟模板中展示了 DISCO。我们还演示了如何有效地将基于图像的变形(DARTEL)与 DISCO 结合使用,以进一步提高配准性能的一致性和准确性。最后,我们说明了如何通过在个体间优化皮质褶皱的对齐来提高在神经影像学数据的组水平分析中检测功能激活的敏感性。