An image registration framework for discontinuous mappings along cracks

Hari Om Aggrawal; Martin S. Andersen; Jan Modersitzki

doi:10.1007/978-3-030-50120-4_16

An image registration framework for discontinuous mappings along cracks

Hari Om Aggrawal^*, Martin S. Andersen, Jan Modersitzki

^*Korrespondierende/r Autor/-in für diese Arbeit

Institut für Mathematische Methoden der Bildverarbeitung

DTU Informatics, Technical University of Denmark

Abstract

A novel crack capable image registration framework is proposed. The approach is designed for registration problems suffering from cracks, gaps, or holes. The approach enables discontinuous transformation fields and also features an automatically computed crack indicator function and therefore does not require a pre-segmentation. The new approach is a generalization of the commonly used variational image registration approach. New contributions are an additional dissipation term in the overall energy, a proper balancing of different ingredients, and a joint optimization for both, the crack indicator function and the transformation. Results for histological serial sectioning of marmoset brain images demonstrate the potential of the approach and its superiority as compared to a standard registration.

Originalsprache	Englisch
Titel	WBIR 2020: Biomedical Image Registration
Redakteure/-innen	Žiga Špiclin, Jamie McClelland, Jan Kybic, Orcun Goksel
Seitenumfang	11
Band	12120 LNCS
Herausgeber (Verlag)	Springer, Cham
Erscheinungsdatum	09.06.2020
Seiten	163-173
ISBN (Print)	978-3-030-50119-8
ISBN (elektronisch)	978-3-030-50120-4
DOIs	https://doi.org/10.1007/978-3-030-50120-4_16
Publikationsstatus	Veröffentlicht - 09.06.2020
Veranstaltung	9th International Workshop on Biomedical Image Registration - Portoroz, Slowenien Dauer: 01.12.2020 → 02.12.2020 Konferenznummer: 240939

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Aggrawal, H. O., Andersen, M. S., & Modersitzki, J. (2020). An image registration framework for discontinuous mappings along cracks. in Ž. Špiclin, J. McClelland, J. Kybic, & O. Goksel (Hrsg.), WBIR 2020: Biomedical Image Registration (Band 12120 LNCS, S. 163-173). (Lecture Notes in Computer Science; Band 12120 LNCS). Springer, Cham. https://doi.org/10.1007/978-3-030-50120-4_16

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title = "An image registration framework for discontinuous mappings along cracks",

abstract = "A novel crack capable image registration framework is proposed. The approach is designed for registration problems suffering from cracks, gaps, or holes. The approach enables discontinuous transformation fields and also features an automatically computed crack indicator function and therefore does not require a pre-segmentation. The new approach is a generalization of the commonly used variational image registration approach. New contributions are an additional dissipation term in the overall energy, a proper balancing of different ingredients, and a joint optimization for both, the crack indicator function and the transformation. Results for histological serial sectioning of marmoset brain images demonstrate the potential of the approach and its superiority as compared to a standard registration.",

author = "Aggrawal, {Hari Om} and Andersen, {Martin S.} and Jan Modersitzki",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 9th International Workshop on Biomedical Image Registration , WBIR 2020 ; Conference date: 01-12-2020 Through 02-12-2020",

year = "2020",

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doi = "10.1007/978-3-030-50120-4_16",

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publisher = "Springer, Cham",

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editor = "{\v S}piclin, {{\v Z}iga } and McClelland, {Jamie } and Kybic, {Jan } and Goksel, {Orcun }",

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Aggrawal, HO, Andersen, MS & Modersitzki, J 2020, An image registration framework for discontinuous mappings along cracks. in Ž Špiclin, J McClelland, J Kybic & O Goksel (Hrsg.), WBIR 2020: Biomedical Image Registration . Bd. 12120 LNCS, Lecture Notes in Computer Science, Bd. 12120 LNCS, Springer, Cham, S. 163-173, 9th International Workshop on Biomedical Image Registration , Portoroz, Slowenien, 01.12.20. https://doi.org/10.1007/978-3-030-50120-4_16

An image registration framework for discontinuous mappings along cracks. / Aggrawal, Hari Om; Andersen, Martin S.; Modersitzki, Jan.
WBIR 2020: Biomedical Image Registration . Hrsg. / Žiga Špiclin; Jamie McClelland; Jan Kybic; Orcun Goksel. Band 12120 LNCS Springer, Cham, 2020. S. 163-173 (Lecture Notes in Computer Science; Band 12120 LNCS).

Publikation: Kapitel in Büchern/Berichten/Konferenzbänden › Konferenzbeitrag › Begutachtung

TY - GEN

T1 - An image registration framework for discontinuous mappings along cracks

AU - Aggrawal, Hari Om

AU - Andersen, Martin S.

AU - Modersitzki, Jan

N1 - Conference code: 240939

PY - 2020/6/9

Y1 - 2020/6/9

N2 - A novel crack capable image registration framework is proposed. The approach is designed for registration problems suffering from cracks, gaps, or holes. The approach enables discontinuous transformation fields and also features an automatically computed crack indicator function and therefore does not require a pre-segmentation. The new approach is a generalization of the commonly used variational image registration approach. New contributions are an additional dissipation term in the overall energy, a proper balancing of different ingredients, and a joint optimization for both, the crack indicator function and the transformation. Results for histological serial sectioning of marmoset brain images demonstrate the potential of the approach and its superiority as compared to a standard registration.

AB - A novel crack capable image registration framework is proposed. The approach is designed for registration problems suffering from cracks, gaps, or holes. The approach enables discontinuous transformation fields and also features an automatically computed crack indicator function and therefore does not require a pre-segmentation. The new approach is a generalization of the commonly used variational image registration approach. New contributions are an additional dissipation term in the overall energy, a proper balancing of different ingredients, and a joint optimization for both, the crack indicator function and the transformation. Results for histological serial sectioning of marmoset brain images demonstrate the potential of the approach and its superiority as compared to a standard registration.

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DO - 10.1007/978-3-030-50120-4_16

M3 - Conference contribution

SN - 978-3-030-50119-8

VL - 12120 LNCS

T3 - Lecture Notes in Computer Science

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BT - WBIR 2020: Biomedical Image Registration

A2 - Špiclin, Žiga

A2 - McClelland, Jamie

A2 - Kybic, Jan

A2 - Goksel, Orcun

PB - Springer, Cham

T2 - 9th International Workshop on Biomedical Image Registration

Y2 - 1 December 2020 through 2 December 2020

ER -

An image registration framework for discontinuous mappings along cracks

Abstract

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