Automatic identificaiton of cortical sulci using a 3D probabilistic atlas

We present an approach which performs the automatic labeling of the main corf;cortical sulci using a priori information for the 3D spatial distribution of these entities. We have developed a methodology to extract the 3D cortical topography of a particular subject from an vivo observations obtained through MRI. The cortical topography is encoded in a relational graph structure composed of two main features: arcs and vertices. Each vertex contains a parametric surface representing the buried part of a sulcus. Points on this parametric surface are expressed in stereotaxic coordinates ( i.e., with respect to a standardized brain co-ordinate system). Arcs represent the connections between these entities. Manual sulcal labeling is performed by tagging a sulcal surface in the 3-D graph and selecting from a menu of candidate sulcus names. Automatic labeling is dependent on a probabilistic atlas of sulcal anatomy derived from a set of 51 graphs that were labeled by an anatomist. We show how these 3D sulcal spatial distribution maps can be used to perform the identification of the cortical sulci. We focus our attention on the peri-central area (including pre-central, post-central and central sulci). Results show that the use of spatial priors permit automatic identification of the main sulci with a good accuracy.