DeepAI AI Chat
Log In Sign Up

A Multi-scale Optimization Learning Framework for Diffeomorphic Deformable Registration

by   Risheng Liu, et al.

Conventional deformable registration methods aim at solving a specifically designed optimization model on image pairs and offer a rigorous theoretical treatment. However, their computational costs are exceptionally high. In contrast, recent learning-based approaches can provide fast deformation estimation. These heuristic network architectures are fully data-driven and thus lack explicitly domain knowledge or geometric constraints, such as topology-preserving, which is indispensable to generate plausible deformations. To integrate the advantages and avoid the limitations of these two categories of approaches, we design a new learning-based framework to optimize a diffeomorphic model via multi-scale propagations. Specifically, we first introduce a generic optimization model to formulate diffeomorphic registration with both velocity and deformation fields. Then we propose a schematic optimization scheme with a nested splitting technique. Finally, a series of learnable architectures are utilized to obtain the final propagative updating in the coarse-to-fine feature spaces. We conduct two groups of image registration experiments on 3D adult and child brain MR volume datasets including image-to-atlas and image-to-image registrations. Extensive results demonstrate that the proposed method achieves state-of-the-art performance with diffeomorphic guarantee and extreme efficiency.


page 1

page 3

page 5

page 7

page 8

page 10


SearchMorph:Multi-scale Correlation Iterative Network for Deformable Registration

Deformable image registration provides dynamic information about the ima...

Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration

Traditional deformable registration techniques achieve impressive result...

Quicksilver: Fast Predictive Image Registration - a Deep Learning Approach

This paper introduces Quicksilver, a fast deformable image registration ...

Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces

Classical deformable registration techniques achieve impressive results ...

Test-Time Training for Deformable Multi-Scale Image Registration

Registration is a fundamental task in medical robotics and is often a cr...

Dual-Stream Pyramid Registration Network

We propose a Dual-Stream Pyramid Registration Network (referred as Dual-...