Recursive Decomposition Network for Deformable Image Registration | IEEE Journals & Magazine | IEEE Xplore

Recursive Decomposition Network for Deformable Image Registration


Abstract:

Deformation decomposition serves as a good solution for deformable image registration when the deformation is large. Current deformation decomposition methods can be cate...Show More

Abstract:

Deformation decomposition serves as a good solution for deformable image registration when the deformation is large. Current deformation decomposition methods can be categorized into cascade-based methods and pyramid-based methods. However, cascade-based methods suffer from heavy computational burdens and long inference time due to their structures of repeated subnetworks, while the effectiveness of pyramid-based methods is constrained by their limited numbers of resolution levels. In this paper, to address both the insufficient and inefficient decomposition problems in current deformation decomposition methods, we propose a recursive decomposition network (RDN) to offer a novel solution for deformable image registration. Stage-wise recursion can efficiently decompose a large deformation into different pyramid estimation stages without using repeated subnetworks like in cascade-based methods. Level-wise recursion can sufficiently decompose the deformation inside each resolution level instead of only one-time estimation like in pyramid-based methods. Extensive experiments and ablation studies on two representative datasets validate the effectiveness and efficiency of our proposed RDN.
Published in: IEEE Journal of Biomedical and Health Informatics ( Volume: 26, Issue: 10, October 2022)
Page(s): 5130 - 5141
Date of Publication: 11 July 2022

ISSN Information:

PubMed ID: 35816523

Funding Agency:


References

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