Differences in brain morphology across population groups necessitate creation of population-specific Magnetic Resonance Imaging (MRI) brain templates for interpretation of neuroimaging data. Variations in the neuroanatomy in a genetically heterogeneous population make the development of a population-specific brain template for the Indian subcontinent imperative. A dataset of high-resolution 3D T1, T2-weighted, and FLAIR images acquired from a group of 113 volunteers (M/F - 56/57, mean age-28.96 ± 7.80 years) are used to construct T1, T2-weighted, and FLAIR templates, collectively referred to as Indian Brain Template, "BRAHMA". A processing pipeline is developed and implemented in a MATLAB based toolbox for template construction and generation of tissue probability maps and segmentation atlases, with additional labels for deep brain regions such as the Substantia Nigra generated from the T2-weighted and FLAIR templates. The use of BRAHMA template for analysis of structural and functional neuroimaging data obtained from Indian participants, provides improved accuracy with statistically significant results over that obtained using the ICBM-152 (International Consortium for Brain Mapping) template. Our results indicate that segmentations generated on structural images are closer in volume to those obtained from registration to the BRAHMA template than to the ICBM-152. Furthermore, functional MRI data obtained for Working Memory and Finger Tapping paradigms processed using the BRAHMA template show a significantly higher percentage of the activation area than ICBM-152 in relevant brain regions, i.e. the left middle frontal gyrus, and the left and right precentral gyri, respectively. The availability of different image contrasts, tissue maps, and segmentation atlases makes the BRAHMA template a comprehensive tool for multi-modal image analysis in laboratory and clinical settings.

中文翻译：

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BRAHMA：特定于人群的T1，T2和FLAIR加权脑模板及其在结构和功能成像研究中的影响。

人群之间脑形态的差异需要创建特定于人群的磁共振成像（MRI）脑模板来解释神经影像数据。遗传异质群体中神经解剖学的变化使得印度次大陆的特定人群脑模板的发展势在必行。从一组113位志愿者（M / F-56/57，平均年龄28.96±7.80岁）中获得的高分辨率3D T1，T2加权和FLAIR图像数据集用于构建T1，T2加权，和FLAIR模板，统称为“印度脑模板”，即“ BRAHMA”。处理流程是在基于MATLAB的工具箱中开发和实现的，用于模板构建以及组织概率图和分割图集的生成，以及用于深部大脑区域的其他标签，例如从T2加权模板和FLAIR模板生成的黑质。使用BRAHMA模板来分析从印度参与者那里获得的结构和功能性神经影像数据，与使用ICBM-152（国际脑图研究联盟）模板所获得的结果相比，具有更高的准确性和统计学上显着的结果。我们的结果表明，在结构图像上生成的分割在体积上比从BRAHMA模板注册获得的分割更接近于ICBM-152。此外，使用BRAHMA模板处理的针对工作记忆和手指敲击范例获得的功能性MRI数据显示，在相关大脑区域（即左中额额回）中，激活区域的百分比显着高于ICBM-152。左和右中央前回。不同的图像对比度，组织图和分割图谱的可用性使BRAHMA模板成为在实验室和临床环境中进行多模式图像分析的综合工具。