English

A method for large diffeomorphic registration via broken geodesics

Computer Vision and Pattern Recognition 2021-01-05 v2

Abstract

Anatomical variabilities seen in longitudinal data or inter-subject data is usually described by the underlying deformation, captured by non-rigid registration of these images. Stationary Velocity Field (SVF) based non-rigid registration algorithms are widely used for registration. SVF based methods form a metric-free framework which captures a finite dimensional submanifold of deformations embedded in the infinite dimensional smooth manifold of diffeomorphisms. However, these methods cover only a limited degree of deformations. In this paper, we address this limitation and define an approximate metric space for the manifold of diffeomorphisms G\mathcal{G}. We propose a method to break down the large deformation into finite compositions of small deformations. This results in a broken geodesic path on G\mathcal{G} and its length now forms an approximate registration metric. We illustrate the method using a simple, intensity-based, log-demon implementation. Validation results of the proposed method show that it can capture large and complex deformations while producing qualitatively better results than the state-of-the-art methods. The results also demonstrate that the proposed registration metric is a good indicator of the degree of deformation.

Keywords

Cite

@article{arxiv.2011.14298,
  title  = {A method for large diffeomorphic registration via broken geodesics},
  author = {Alphin J. Thottupattu and Jayanthi Sivaswamy and Venkateswaran P. Krishnan},
  journal= {arXiv preprint arXiv:2011.14298},
  year   = {2021}
}

Comments

18 pages and 9 figures

R2 v1 2026-06-23T20:34:34.213Z