What is MNI_AutoReg?

In both diagnostic and research applications, the interpretation of magnetic resonance (MR) images of the human brain is facilitated when different data sets can be compared by visual inspection of equivalent anatomical planes. Quantitative analysis with pre-defined atlas templates often requires the initial alignment of atlas and image planes. Unfortunately, the axial planes acquired during separate scanning sessions are often different in their relative position and orientation, and these slices are not coplanar with those in the atlas. A completely automatic method has been developed, based on multi-scale, three dimensional (3D) cross-correlation, to register a given volumetric data set to an average MRI brain (n > 300) aligned with the Talairach stereotaxic coordinate system. Once the data set is resampled by the transformation recovered by the algorithm, atlas slices can be directly super-imposed on the corresponding slices of the resampled volume (see below). The use of such a standardized space also allows the direct comparison, voxel-to-voxel, of two or more data sets brought into stereotaxic space.

A Perl script (mritotal) implements the multi-resolution fitting strategy that has been used to map more than 500 brains into stereotaxic space at the Montreal Neurological Institute. At the heart of this procedure is minctracc, the program that automatically finds the best linear transformation to map one volumetric data set (stored in MINC format, see below) on to another. The program uses optimization over a user selectable number of parameters to identify the best (according to a user-selected objective function) transformation mapping voxel values of the first data set into the second.