Deep brain stimulation (DBS) therapy requires extensive patient-specific planning prior to implantation to achieve optimal clinical outcomes. Collective analysis of patient's brain images is promising in order to provide more systematic planning assistance. In this paper the design of a normalization pipeline using a group specific multi-modality iterative template creation process is presented. The focus was to compare the performance of a selection of freely available registration tools and select the best combination. The workflow was applied on 19 DBS patients with T1 and WAIR modality images available. Non-linear registrations were computed with ANTS, FNIRT and DRAMMS, using several settings from the literature. Registration accuracy was measured using single-expert labels of thalamic and subthalamic structures and their agreement across the group. The best performance was provided by ANTS using the High Variance settings published elsewhere. Neither FNIRT nor DRAMMS reached the level of performance of ANTS. The resulting normalized definition of anatomical structures were used to propose an atlas of the diencephalon region defining 58 structures using data from 19 patients.

中文翻译：

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大脑解剖结构正常化，用于运动障碍中的深部大脑刺激。

深部脑刺激（DBS）治疗需要在植入患者之前进行广泛的针对患者的计划，以实现最佳的临床效果。对患者的大脑图像进行集体分析很有希望，以便提供更系统的计划协助。在本文中，提出了使用特定于组的多模态迭代模板创建过程的规范化管道的设计。重点是比较各种免费注册工具的性能并选择最佳组合。该工作流程已应用于19名具有T1和WAIR模态图像的DBS患者。使用文献中的几种设置，使用ANTS，FNIRT和DRAMMS计算非线性配准。使用丘脑和丘脑底结构的单一专家标签及其在整个研究组中的一致性来测量注册准确性。ANTS使用在其他位置发布的“高方差”设置提供了最佳性能。FNIRT和DRAMMS均未达到ANTS的性能水平。所得到的解剖结构的标准化定义被用来使用19个患者的数据提出定义58个结构的中脑区域地图集。