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

^*Corresponding author for this work

Institute of Mathematics and Image Computing

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.

Original language	English
Title of host publication	WBIR 2020: Biomedical Image Registration
Editors	Žiga Špiclin, Jamie McClelland, Jan Kybic, Orcun Goksel
Number of pages	11
Volume	12120 LNCS
Publisher	Springer, Cham
Publication date	09.06.2020
Pages	163-173
ISBN (Print)	978-3-030-50119-8
ISBN (Electronic)	978-3-030-50120-4
DOIs	https://doi.org/10.1007/978-3-030-50120-4_16
Publication status	Published - 09.06.2020
Event	9th International Workshop on Biomedical Image Registration - Portoroz, Slovenia Duration: 01.12.2020 → 02.12.2020 Conference number: 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 (Eds.), WBIR 2020: Biomedical Image Registration (Vol. 12120 LNCS, pp. 163-173). (Lecture Notes in Computer Science; Vol. 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",

language = "English",

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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 (eds), WBIR 2020: Biomedical Image Registration . vol. 12120 LNCS, Lecture Notes in Computer Science, vol. 12120 LNCS, Springer, Cham, pp. 163-173, 9th International Workshop on Biomedical Image Registration , Portoroz, Slovenia, 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 . ed. / Žiga Špiclin; Jamie McClelland; Jan Kybic; Orcun Goksel. Vol. 12120 LNCS Springer, Cham, 2020. p. 163-173 (Lecture Notes in Computer Science; Vol. 12120 LNCS).

Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

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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U2 - 10.1007/978-3-030-50120-4_16

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

SP - 163

EP - 173

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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