Department of Neurophysiology, Nencki Institute of Experimental Biology, 3 Pasteur Street, 02-093, Warsaw, Poland.
Neuroinformatics. 2012 Apr;10(2):181-97. doi: 10.1007/s12021-011-9138-6.
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.
现代神经科学面临的挑战之一是整合来自各种样本的不同模式的大量数据。这项任务需要一个通用的空间框架，而大脑图谱可以提供这种框架。最初的图谱仅限于二维结构数据的呈现。最近，人们尝试创建 3D 图谱，以提供在非标准解剖平面内的导航，并提高大脑体积中不同类型数据的定位能力。到目前为止，可用的 3D 图谱是使用难以让其他研究人员复制结果的框架创建的。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 的通用图谱格式（CAF），用于存储 2D 图谱描绘或其他兼容数据，以及 3D 大脑图谱重构器（3dBAR），这是一种专门用于从 2D 图谱数据自动重建三维大脑结构的软件。基本功能由以下部分提供：(1) 一组解析器，用于将各种图谱从多种格式转换为 CAF；(2) 一个从 CAF 数据集生成 3D 模型的模块。整个重建过程是可重复的，并且可以轻松进行配置、跟踪和审查，这有助于纠正错误。当自动重建不足时，可以进行手动更正。该软件旨在通过使用开放文件格式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。
