| 11 | | One of the challenges of modern neuroscience is integrating voluminous |
| 12 | | data of diferent modalities derived from a variety of specimens. This |
| 13 | | task requires a common spatial framework that can be provided by brain |
| 14 | | atlases. The first atlases were limited to two-dimentional |
| 15 | | presentation of structural data. Recently, attempts at creating 3D |
| 16 | | atlases have been made to offer navigation within non-standard |
| 17 | | anatomical planes and improve capability of localization of different |
| 18 | | types of data within the brain volume. |
| 19 | | |
| 20 | | The 3D atlases available so far have been created using frameworks |
| 21 | | which make it difficult for other researchers to replicate the |
| 22 | | results. To facilitate reproducible research and data sharing in the |
| 23 | | field we propose an SVG-based Common Atlas Format (CAF) to store 2D |
| 24 | | atlas delineations or other compatible data and 3D Brain Atlas |
| 25 | | Reconstructor (3dBAR), software dedicated to automated |
| 26 | | reconstruction of three-dimensional brain structures from 2D atlas |
| 27 | | data. The basic functionality is provided by 1) a set of parsers which |
| 28 | | translate various atlases from a number of formats into the CAF, and |
| 29 | | 2) a module generating 3D models from CAF datasets. |
| 30 | | |
| 31 | | The whole reconstruction process is reproducible and can easily be |
| 32 | | configured, tracked and reviewed, which facilitates fixing |
| 33 | | errors. Manual corrections can be made when automatic reconstruction |
| 34 | | is not sufficient. The software was designed to simplify |
| 35 | | interoperability with other neuroinformatics tools by using open file |
| 36 | | formats. The content can easily be exchanged at any stage of data |
| 37 | | processing. The framework allows for the addition of new public or |
| 38 | | proprietary content. |
| | 9 | (...) |
