Gaussian primitives for deformable image registration.

ABSTRACT:

Background and purpose

Deformable image registration (DIR) plays a critical role in radiotherapy by compensating for anatomical deformations. However, existing iterative and data-driven methods are often hindered by computational inefficiency or limited generalization. In response, our objective was to develop a novel optimization-based DIR method that reduces computational overhead and preserves the robust generalization of iterative methods while enhancing interpretability.

Materials and methods

We proposed GaussianDIR, a novel DIR framework that explicitly represents the deformation field using a sparse set of adaptive Gaussian primitives. Each primitive is characterized by its centre, covariance, and associated local rigid deformation. Voxel-wise displacements are derive

SUBMITTER: Li J 

PROVIDER: S-EPMC12361785 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature