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Common Atlas Format and 3D Brain Atlas Reconstructor: Infrastructure for Constructing 3D Brain Atlases

机译:常见的Atlas格式和3D脑图集重构器:构建3D脑图集的基础结构

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摘要

One of the challenges of modern neuroscience is integrating voluminous data of diferent modalities derived from a variety of specimens. This task requires a common spatial framework that can be provided by brain atlases. The first atlases were limited to two-dimentional presentation of structural data. Recently, attempts at creating 3D atlases have been made to offer navigation within non-standard anatomical planes and improve capability of localization of different types of data within the brain volume. The 3D atlases available so far have been created using frameworks which make it difficult for other researchers to replicate the results. To facilitate reproducible research and data sharing in the field we propose an SVG-based Common Atlas Format (CAF) to store 2D atlas delineations or other compatible data and 3D Brain Atlas Reconstructor (3dBAR), software dedicated to automated reconstruction of three-dimensional brain structures from 2D atlas data. The basic functionality is provided by (1) a set of parsers which translate various atlases from a number of formats into the CAF, and (2) a module generating 3D models from CAF datasets. The whole reconstruction process is reproducible and can easily be configured, tracked and reviewed, which facilitates fixing errors. Manual corrections can be made when automatic reconstruction is not sufficient. The software was designed to simplify interoperability with other neuroinformatics tools by using open file formats. The content can easily be exchanged at any stage of data processing. The framework allows for the addition of new public or proprietary content.>Electronic supplementary material The online version of this article (doi:10.1007/s12021-011-9138-6) contains supplementary material, which is available to authorized users.
机译:现代神经科学的挑战之一是整合来自各种标本的不同模态的大量数据。这项任务需要可以由脑图集提供的通用空间框架。最初的地图集仅限于二维呈现结构数据。最近,已尝试创建3D地图集,以在非标准解剖平面内提供导航,并提高大脑体积内不同类型数据的定位能力。到目前为止,已使用框架创建了可用的3D地图集,这使其他研究人员难以复制结果。为了促进该领域的可重复性研究和数据共享,我们提出了一种基于SVG的通用地图集格式(CAF),用于存储2D地图集描述或其他兼容数据以及3D Brain Atlas Reconstructor(3dBAR),这是一种用于自动重建三维大脑的软件来自2D地图集数据的结构。基本功能由(1)一组解析器将各种地图集从多种格式转换为CAF,以及(2)从CAF数据集生成3D模型的模块提供。整个重建过程是可重现的,并且可以轻松配置,跟踪和检查,这有助于修复错误。当自动重建不足时,可以进行手动校正。该软件旨在通过使用开放文件格式来简化与其他神经信息学工具的互操作性。内容可以在数据处理的任何阶段轻松交换。该框架允许添加新的公共或专有内容。>电子补充材料本文的在线版本(doi:10.1007 / s12021-011-9138-6)包含补充材料,可用于授权用户。

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