@inproceedings{3194c71d986b40e0a612c4bef6d7749c,
title = "Metamorphic Image Registration Using a Semi-lagrangian Scheme",
abstract = "In this paper, we propose an implementation of both Large Deformation Diffeomorphic Metric Mapping (LDDMM) and Metamorphosis image registration using a semi-Lagrangian scheme for geodesic shooting. We propose to solve both problems as an inexact matching providing a single and unifying cost function. We demonstrate that for image registration the use of a semi-Lagrangian scheme is more stable than a standard Eulerian scheme. Our GPU implementation is based on PyTorch, which greatly simplifies and accelerates the computations thanks to its powerful automatic differentiation engine. It will be freely available at https://github.com/antonfrancois/Demeter\_metamorphosis.",
keywords = "Image diffeomorphic registration, LDDMM, Metamorphosis, Semi-Lagrangian scheme",
author = "Anton Fran{\c c}ois and Pietro Gori and Joan Glaun{\`e}s",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 5th International Conference on Geometric Science of Information, GSI 2021 ; Conference date: 21-07-2021 Through 23-07-2021",
year = "2021",
month = jan,
day = "1",
doi = "10.1007/978-3-030-80209-7\_84",
language = "English",
isbn = "9783030802080",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "781--788",
editor = "Frank Nielsen and Fr{\'e}d{\'e}ric Barbaresco",
booktitle = "Geometric Science of Information - 5th International Conference, GSI 2021, Proceedings",
}