Section: New Results

Registration of brain images based on Currents

Participants : Pierre Fillard, Bertrand Thirion, Viviana Siless [correspondant] .

We present an extension of the diffeomorphic Geometric Demons algorithm which combines the iconic registration with geometric constraints. Our algorithm works in the log-domain space, so that one can efficiently compute the deformation field of the geometry. We represent the shape of objects of interest in the space of currents which is sensitive to both location and geometric structure of objects. Currents provide a distance between geometric structures that can be defined without specifying explicit point-to-point correspondences. We demonstrate this framework by registering simultaneously T1 images and 65 fiber bundles consistently extracted in 12 subjects and compare it against non-linear T1, tensor, and multi-modal T1+ Fractional Anisotropy (FA) registration algorithms. Results show the superiority of the Log-domain Geometric Demons over their purely iconic counterparts.

Figure 5. Comparison of the fiber registration through various algorithms. We display a moving and a reference fiber for 29 selected bundles. The proposed approach (SLDD) outperforms state-of-the art alternatives that do not take into account the fiber geometry explicitly.

More details can be found in [31] .