McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, H3A 2B4, 514-398-4227, Quebec (QC), Canada.
Sci Data. 2020 Jul 15;7(1):237. doi: 10.1038/s41597-020-0557-9.
Accurate anatomical atlases are recognized as important tools in brain-imaging research. They are widely used to estimate disease-specific changes and therefore, are of great relevance in extracting regional information on volumetric variations in clinical cohorts in comparison to healthy populations. The use of high spatial resolution magnetic resonance imaging and the improvement in data preprocessing methods have enabled the study of structural volume changes on a wide range of disorders, particularly in neurodegenerative diseases where different brain morphometry analyses are being broadly used in an effort to improve diagnostic biomarkers. In the present dataset, we introduce the Cerebrum Atlas (CerebrA) along with the MNI-ICBM2009c average template. MNI-ICBM2009c is the most recent version of the MNI-ICBM152 brain average, providing a higher level of anatomical details. Cerebra is based on an accurate non-linear registration of cortical and subcortical labelling from Mindboggle 101 to the symmetric MNI-ICBM2009c atlas, followed by manual editing.
准确的解剖图谱被认为是脑成像研究中的重要工具。它们被广泛用于估计特定疾病的变化,因此,在与健康人群相比,从临床队列中提取关于体积变化的区域信息方面具有重要意义。高空间分辨率磁共振成像的使用和数据预处理方法的改进,使得对广泛的疾病的结构体积变化的研究成为可能,特别是在神经退行性疾病中,正在广泛使用不同的脑形态计量学分析,以努力改善诊断生物标志物。在本数据集,我们引入了大脑图谱(CerebrA)以及 MNI-ICBM2009c 平均模板。MNI-ICBM2009c 是 MNI-ICBM152 大脑平均的最新版本,提供了更高水平的解剖细节。Cerebra 是基于 Mindboggle 101 到对称 MNI-ICBM2009c 图谱的皮质和皮质下标记的精确非线性配准,然后进行手动编辑。