General Approach to Nonrigid Registration: Decoupled Optimization.

摘要

To a great extent the success of advanced image-guided medical procedures hinges on non-rigid volume registration. For example non-rigid registration must be applied in interventional approaches where intra-operative information is used to update high-quality preoperative data; in follow-up studies in order to assess time-evolution of development; aging pathology or treatment; and in many other applications including intersubject variability and population-based atlas construction. In this paper we examine several computational schemes that warps one volumetric dataset onto another. We also explore the inevitable trade-off between the computational load and the incorporation of sophisticated similarity measures necessary for multimodal volumes. Estimated deformation fields are based on the variational formulation of Partial Derivative Equations (PDEs) which includes a similarity, and a regularization term. We compare numerical solutions to this problem using the Euler-Lagrange equations (EL) the Finite Elements discretization (FE) and Decoupled Optimization over the possible deformations (DO).