Importation in BrainVISA database

Processes in this category are to be used to import your data in one of the configured BrainVISA database. Theses processes takes files on your file system and copy them in a BrainVISA database.

Subcategories

There are several subcategories in import :

T1 MRI: import T1-weighted MRI.
Diffusion and Tracking: import diffusion MR images. (Available with Diffusion and Tracking toolbox)

What does an import process do ?

Each import process is designed for a specific data type and possibly for a specific data provider (scanner, software, etc.). The process ask the user to specify information that are required to process the data but cannot be extracted from the input files. Then it writes this information along with the data in the BrainVISA database.

How added information are stored in the database ?

Since BrainVISA and Aims library (C++ processing library) can recognize various file formats (DICOM, Nifti, SPM/Analyse, GIS, MINC, etc.), we chose to create a meta-header that can be attached to any file (not only images) and that can contain any structured information. The extension for this header is '.minf' and its actual format is an ascii version of a Python dictionary (in the future it will be an XML file). First, information stored in the image is extracted from its format (volume dimensions, voxel sizes, etc.). Then, this information is completed by the content of the minf file. The name of the minf file is the concatenation of the name of the first file of the image format (in BrainVISA definiton order) and '.minf' extension. For example SPM format is defined with *.img and *.hdr extension. Therefore, SPM readers will use the following files :

*.img
*.hdr
*.img.minf (if it exists)

Here is an example to illustrate the structure of a *.minf file:

  attributes = {
      'ascii' : 0,
      'byte_swapping' : 1,
      'data_type' : 'S16',
      'file_type' : 'GIS',
      'object_type' : 'Volume',
      'volume_dimension' : [ 256, 256, 124, 1 ],
      'voxel_size' : [ 1.01562, 1.01562, 1.1, 1 ]
    }