Rank constrained diffeomorphic density motion estimation for respiratory correlated computed tomography

Markus Foote; Pouya Sabouri; Amit Sawant; Sarang Joshi

doi:10.1007/978-3-319-67675-3_16

Rank constrained diffeomorphic density motion estimation for respiratory correlated computed tomography

Markus Foote, Pouya Sabouri, Amit Sawant, Sarang Joshi

Radiation Oncology

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

1 Scopus citations

Abstract

Motion estimation of organs in a sequence of images is important in numerous medical imaging applications. The focus of this paper is the analysis of 4D Respiratory Correlated Computed Tomography (RCCT) Imaging. It is hypothesized that the quasi-periodic breathing induced motion of organs in the thorax can be represented by deformations spanning a very low dimension subspace of the full infinite dimensional space of diffeomorphic transformations. This paper presents a novel motion estimation algorithm that includes the constraint for low-rank motion between the different phases of the RCCT images. Low-rank deformation solutions are necessary for the efficient statistical analysis and improved treatment planning and delivery. Although the application focus of this paper is RCCT the algorithm is quite general and applicable to various motion estimation problems in medical imaging.

Original language	English (US)
Title of host publication	Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - 1st International Workshop, GRAIL 2017 6th International Workshop, MFCA 2017 and 3rd International Workshop, MICGen 2017 Held in Conjunction with MICCAI 2017, Proceedings
Editors	M. Jorge Cardoso, Tal Arbel
Publisher	Springer Verlag
Pages	177-185
Number of pages	9
ISBN (Print)	9783319676746
DOIs	https://doi.org/10.1007/978-3-319-67675-3_16
State	Published - 2017
Event	1st International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017, 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017 and 3rd International Workshop on Imaging Genetics, MICGen 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017 - Quebec City, Canada Duration: Sep 10 2017 → Sep 14 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10551 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	1st International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017, 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017 and 3rd International Workshop on Imaging Genetics, MICGen 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017
Country/Territory	Canada
City	Quebec City
Period	9/10/17 → 9/14/17

Keywords

Diffeomorphisms
Image registration

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-67675-3_16

Cite this

Foote, M., Sabouri, P., Sawant, A., & Joshi, S. (2017). Rank constrained diffeomorphic density motion estimation for respiratory correlated computed tomography. In M. J. Cardoso, & T. Arbel (Eds.), Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - 1st International Workshop, GRAIL 2017 6th International Workshop, MFCA 2017 and 3rd International Workshop, MICGen 2017 Held in Conjunction with MICCAI 2017, Proceedings (pp. 177-185). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10551 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-67675-3_16

Rank constrained diffeomorphic density motion estimation for respiratory correlated computed tomography. / Foote, Markus; Sabouri, Pouya; Sawant, Amit et al.
Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - 1st International Workshop, GRAIL 2017 6th International Workshop, MFCA 2017 and 3rd International Workshop, MICGen 2017 Held in Conjunction with MICCAI 2017, Proceedings. ed. / M. Jorge Cardoso; Tal Arbel. Springer Verlag, 2017. p. 177-185 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10551 LNCS).

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

Foote, M, Sabouri, P, Sawant, A & Joshi, S 2017, Rank constrained diffeomorphic density motion estimation for respiratory correlated computed tomography. in MJ Cardoso & T Arbel (eds), Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - 1st International Workshop, GRAIL 2017 6th International Workshop, MFCA 2017 and 3rd International Workshop, MICGen 2017 Held in Conjunction with MICCAI 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10551 LNCS, Springer Verlag, pp. 177-185, 1st International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017, 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017 and 3rd International Workshop on Imaging Genetics, MICGen 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017, Quebec City, Canada, 9/10/17. https://doi.org/10.1007/978-3-319-67675-3_16

Foote M, Sabouri P, Sawant A, Joshi S. Rank constrained diffeomorphic density motion estimation for respiratory correlated computed tomography. In Cardoso MJ, Arbel T, editors, Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - 1st International Workshop, GRAIL 2017 6th International Workshop, MFCA 2017 and 3rd International Workshop, MICGen 2017 Held in Conjunction with MICCAI 2017, Proceedings. Springer Verlag. 2017. p. 177-185. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-67675-3_16

Foote, Markus ; Sabouri, Pouya ; Sawant, Amit et al. / Rank constrained diffeomorphic density motion estimation for respiratory correlated computed tomography. Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - 1st International Workshop, GRAIL 2017 6th International Workshop, MFCA 2017 and 3rd International Workshop, MICGen 2017 Held in Conjunction with MICCAI 2017, Proceedings. editor / M. Jorge Cardoso ; Tal Arbel. Springer Verlag, 2017. pp. 177-185 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Motion estimation of organs in a sequence of images is important in numerous medical imaging applications. The focus of this paper is the analysis of 4D Respiratory Correlated Computed Tomography (RCCT) Imaging. It is hypothesized that the quasi-periodic breathing induced motion of organs in the thorax can be represented by deformations spanning a very low dimension subspace of the full infinite dimensional space of diffeomorphic transformations. This paper presents a novel motion estimation algorithm that includes the constraint for low-rank motion between the different phases of the RCCT images. Low-rank deformation solutions are necessary for the efficient statistical analysis and improved treatment planning and delivery. Although the application focus of this paper is RCCT the algorithm is quite general and applicable to various motion estimation problems in medical imaging.",

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AB - Motion estimation of organs in a sequence of images is important in numerous medical imaging applications. The focus of this paper is the analysis of 4D Respiratory Correlated Computed Tomography (RCCT) Imaging. It is hypothesized that the quasi-periodic breathing induced motion of organs in the thorax can be represented by deformations spanning a very low dimension subspace of the full infinite dimensional space of diffeomorphic transformations. This paper presents a novel motion estimation algorithm that includes the constraint for low-rank motion between the different phases of the RCCT images. Low-rank deformation solutions are necessary for the efficient statistical analysis and improved treatment planning and delivery. Although the application focus of this paper is RCCT the algorithm is quite general and applicable to various motion estimation problems in medical imaging.

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Rank constrained diffeomorphic density motion estimation for respiratory correlated computed tomography

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