Coupling dense and landmark-based approaches for nonrigid registration
In this paper, we investigate the introduction of cortical constraints for non rigid intersubject brain registration. We extract sulcal patterns with the active ribbon method, presented by Le Goualher et al. (1997). An energy based registration method (Hellier et al., 2001), which will be called photometric registration method in this paper, makes it possible to incorporate the matching of cortical sulci. The local sparse similarity and the photometric similarity are, thus, expressed in a unified framework. We show the benefits of cortical constraints on a database of 18 subjects, with global and local assessment of the registration. This new registration scheme has also been evaluated on functional magnetoencephalography data. We show that the anatomically constrained registration leads to a substantial reduction of the intersubject functional variability.
registration cortical constraints atlas matching multigrid minimization robust estimators