Minimally deformed correspondences between surfaces for intra-operative registration

Range imaging modalities, such as time-of-flight cameras (ToF), are becoming very popular for the acquisition of intra-operative data, which can be used for registering the patient's anatomy with pre-operative data, such as 3D images generated by computed tomographies (CT) or magnetic resonance imaging (MRI). However, due to the distortions that appear because of the different acquisition principles of the input surfaces, the noise, and the deformations that may occur in the intra-operative environment, we face different surface properties for points lying on the same anatomical locations and unreliable feature points detection, which are crucial for most surface matching algorithms. In order to overcome these issues, we present a method for automatically finding correspondences between surfaces that searches for minimally deformed configurations. For this purpose, an error metric that expresses the reliability of a correspondence set based on its spatial configuration is employed. The registration error is minimized by a combinatorial analysis through search-trees. Our method was evaluated with real and simulated ToF and CT data, and showed to be reliable for the registration of partial multi-modal surfaces with noise and distortions.