Slice-to-volume parametric image registration models with applications to cardiac MRI

A mathematical formulation for intensity-based slice-to-volume registration is proposed. The approach is flexible and accommodates various regularization schemes, similarity measures, and optimizers. The framework is evaluated by registering 2D and 3D cardiac magnetic resonance (MR) images obtained in vivo, aimed at realtime MR-guided applications. Rigid-body and affine transformations are used to validate the parametric model. Target registration error (TRE), Jaccard, and Dice indices are used to evaluate the algorithm and demonstrate the accuracy of the registration scheme on both simulated and clinical data. Registration with the affine model appeared to be more robust than with the rigid model in controlled cases. By simply extending the rigid model to an affine model, alignment of the cardiac region generally improved, without the need for complex dissimilarity measures or regularizers.