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A Method for Image Registration via Broken Geodesics

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Part of the Lecture Notes in Computer Science book series (LNCS,volume 13386)


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. However, these methods cover only a limited degree of deformations. We address this limitation and define an approximate metric space for the manifold of diffeomorphisms \(\mathcal {G}\). We propose a method to break down the large deformation into finite set of small sequential deformations. This results in a broken geodesic path on \(\mathcal {G}\) 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 state-of-the-art methods. The results also demonstrate that the proposed registration metric is a good indicator of the degree of deformation.


  • Large deformation
  • Inter-subject registration
  • Approximate registration metric

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Correspondence to Alphin J. Thottupattu .

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Thottupattu, A.J., Sivaswamy, J., Krishnan, V.P. (2022). A Method for Image Registration via Broken Geodesics. In: Hering, A., Schnabel, J., Zhang, M., Ferrante, E., Heinrich, M., Rueckert, D. (eds) Biomedical Image Registration. WBIR 2022. Lecture Notes in Computer Science, vol 13386. Springer, Cham.

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  • Print ISBN: 978-3-031-11202-7

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