Weighted Metamorphosis for Registration of Images with Different Topologies

Anton François; Matthis Maillard; Catherine Oppenheim; Johan Pallud; Isabelle Bloch; Pietro Gori; Joan Glaunès

doi:10.1007/978-3-031-11203-4_2

Weighted Metamorphosis for Registration of Images with Different Topologies

Anton François
, Matthis Maillard
, Catherine Oppenheim
, Johan Pallud
, Isabelle Bloch
, Pietro Gori
, Joan Glaunès

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We present an extension of the Metamorphosis algorithm to align images with different topologies and/or appearances. We propose to restrict/limit the metamorphic intensity additions using a time-varying spatial weight function. It can be used to model prior knowledge about the topological/appearance changes (e.g., tumour/oedema). We show that our method improves the disentanglement between anatomical (i.e., shape) and topological (i.e., appearance) changes, thus improving the registration interpretability and its clinical usefulness. As clinical application, we validated our method using MR brain tumour images from the BraTS 2021 dataset. We showed that our method can better align healthy brain templates to images with brain tumours than existing state-of-the-art methods. Our PyTorch code is freely available here: https://github.com/antonfrancois/Demeter_metamorphosis.

Original language	English
Title of host publication	Biomedical Image Registration - 10th International Workshop, WBIR 2022, Proceedings
Editors	Alessa Hering, Julia Schnabel, Miaomiao Zhang, Enzo Ferrante, Mattias Heinrich, Daniel Rueckert
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	8-17
Number of pages	10
ISBN (Print)	9783031112027
DOIs	https://doi.org/10.1007/978-3-031-11203-4_2
Publication status	Published - 1 Jan 2022
Event	10th International Workshop on Biomedical Image Registration, WBIR 2020 - Munich, Germany Duration: 10 Jul 2022 → 12 Jul 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13386 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Workshop on Biomedical Image Registration, WBIR 2020
Country/Territory	Germany
City	Munich
Period	10/07/22 → 12/07/22

Keywords

Brain tumour
Image registration
Metamorphosis
Topology variation

Access to Document

10.1007/978-3-031-11203-4_2

Cite this

François, A., Maillard, M., Oppenheim, C., Pallud, J., Bloch, I., Gori, P., & Glaunès, J. (2022). Weighted Metamorphosis for Registration of Images with Different Topologies. In A. Hering, J. Schnabel, M. Zhang, E. Ferrante, M. Heinrich, & D. Rueckert (Eds.), Biomedical Image Registration - 10th International Workshop, WBIR 2022, Proceedings (pp. 8-17). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13386 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-11203-4_2

François, Anton ; Maillard, Matthis ; Oppenheim, Catherine et al. / Weighted Metamorphosis for Registration of Images with Different Topologies. Biomedical Image Registration - 10th International Workshop, WBIR 2022, Proceedings. editor / Alessa Hering ; Julia Schnabel ; Miaomiao Zhang ; Enzo Ferrante ; Mattias Heinrich ; Daniel Rueckert. Springer Science and Business Media Deutschland GmbH, 2022. pp. 8-17 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{c80d243e9a004ad9a7622ffa7ef10e72,

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abstract = "We present an extension of the Metamorphosis algorithm to align images with different topologies and/or appearances. We propose to restrict/limit the metamorphic intensity additions using a time-varying spatial weight function. It can be used to model prior knowledge about the topological/appearance changes (e.g., tumour/oedema). We show that our method improves the disentanglement between anatomical (i.e., shape) and topological (i.e., appearance) changes, thus improving the registration interpretability and its clinical usefulness. As clinical application, we validated our method using MR brain tumour images from the BraTS 2021 dataset. We showed that our method can better align healthy brain templates to images with brain tumours than existing state-of-the-art methods. Our PyTorch code is freely available here: https://github.com/antonfrancois/Demeter\_metamorphosis.",

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author = "Anton Fran{\c c}ois and Matthis Maillard and Catherine Oppenheim and Johan Pallud and Isabelle Bloch and Pietro Gori and Joan Glaun{\`e}s",

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François, A, Maillard, M, Oppenheim, C, Pallud, J, Bloch, I, Gori, P & Glaunès, J 2022, Weighted Metamorphosis for Registration of Images with Different Topologies. in A Hering, J Schnabel, M Zhang, E Ferrante, M Heinrich & D Rueckert (eds), Biomedical Image Registration - 10th International Workshop, WBIR 2022, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13386 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 8-17, 10th International Workshop on Biomedical Image Registration, WBIR 2020, Munich, Germany, 10/07/22. https://doi.org/10.1007/978-3-031-11203-4_2

Weighted Metamorphosis for Registration of Images with Different Topologies. / François, Anton; Maillard, Matthis; Oppenheim, Catherine et al.
Biomedical Image Registration - 10th International Workshop, WBIR 2022, Proceedings. ed. / Alessa Hering; Julia Schnabel; Miaomiao Zhang; Enzo Ferrante; Mattias Heinrich; Daniel Rueckert. Springer Science and Business Media Deutschland GmbH, 2022. p. 8-17 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13386 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Weighted Metamorphosis for Registration of Images with Different Topologies

AU - François, Anton

AU - Maillard, Matthis

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AU - Pallud, Johan

AU - Bloch, Isabelle

AU - Gori, Pietro

AU - Glaunès, Joan

PY - 2022/1/1

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N2 - We present an extension of the Metamorphosis algorithm to align images with different topologies and/or appearances. We propose to restrict/limit the metamorphic intensity additions using a time-varying spatial weight function. It can be used to model prior knowledge about the topological/appearance changes (e.g., tumour/oedema). We show that our method improves the disentanglement between anatomical (i.e., shape) and topological (i.e., appearance) changes, thus improving the registration interpretability and its clinical usefulness. As clinical application, we validated our method using MR brain tumour images from the BraTS 2021 dataset. We showed that our method can better align healthy brain templates to images with brain tumours than existing state-of-the-art methods. Our PyTorch code is freely available here: https://github.com/antonfrancois/Demeter_metamorphosis.

AB - We present an extension of the Metamorphosis algorithm to align images with different topologies and/or appearances. We propose to restrict/limit the metamorphic intensity additions using a time-varying spatial weight function. It can be used to model prior knowledge about the topological/appearance changes (e.g., tumour/oedema). We show that our method improves the disentanglement between anatomical (i.e., shape) and topological (i.e., appearance) changes, thus improving the registration interpretability and its clinical usefulness. As clinical application, we validated our method using MR brain tumour images from the BraTS 2021 dataset. We showed that our method can better align healthy brain templates to images with brain tumours than existing state-of-the-art methods. Our PyTorch code is freely available here: https://github.com/antonfrancois/Demeter_metamorphosis.

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KW - Image registration

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Biomedical Image Registration - 10th International Workshop, WBIR 2022, Proceedings

A2 - Hering, Alessa

A2 - Schnabel, Julia

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A2 - Ferrante, Enzo

A2 - Heinrich, Mattias

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PB - Springer Science and Business Media Deutschland GmbH

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François A, Maillard M, Oppenheim C, Pallud J, Bloch I, Gori P et al. Weighted Metamorphosis for Registration of Images with Different Topologies. In Hering A, Schnabel J, Zhang M, Ferrante E, Heinrich M, Rueckert D, editors, Biomedical Image Registration - 10th International Workshop, WBIR 2022, Proceedings. Springer Science and Business Media Deutschland GmbH. 2022. p. 8-17. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-11203-4_2