Dense deformation field estimation for brain intraoperative images registration
Mathieu S. De Craene, A. du Bois d'Aische, Ion‐Florin Talos, Matthieu Ferrant, Peter M. Black, Ferenc Andras Jolesz, Ron Kikinis, Benoit M. M. Macq, Simon Keith Warfield · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
A new fast non rigid registration algorithm is presented. The algorithm estimates a dense deformation field by optimizing a criterion that measures image similarity by mutual information and regularizes with a linear elastic energy term. The optimal deformation field is found using a Simultaneous Perturbation Stochastic Approximation to the gradient. The implementation is parallelized for symmetric multi-processor architectures. This algorithm was applied to capture non-rigid brain deformations that occur during neurosurgery. Segmentation of the intra-operative data is not required but preoperative segmentation of the brain allows the algorithm to be robust to artifacts due to the craniotomy.