Automated Registration of 3D TEE Datasets of the Descending Aorta for Improved Examination and Quantification of Atheromas Burden

M. C. Carminati; C. Piazzese; L. Weinert; W. Tsang; G. Tamborini; M. Pepi; R. M. Lang; E. G. Caiani

doi:10.1007/978-3-319-08554-8_9

Automated Registration of 3D TEE Datasets of the Descending Aorta for Improved Examination and Quantification of Atheromas Burden

M. C. Carminati, C. Piazzese, L. Weinert, W. Tsang, G. Tamborini, M. Pepi, R. M. Lang, E. G. Caiani

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

2 Citations (Scopus)

Abstract

We propose a robust and efficient approach for the reconstruction of the descending aorta from contiguous 3D transesophageal echocardiographic (TEE) images. It is based on an ad hoc protocol, designed to acquire ordered and partially overlapped 3D TEE datasets, followed by automated image registration that relies on this a priori knowledge. The method was validated using artificially derived misaligned images, and then applied to 14 consecutive patients. Both qualitative and quantitative results demonstrated the potential feasibility and accuracy of the proposed approach. Its clinical applicability could improve the assessment of aortic total plaque burden from 3D TEE images.

Original language	English
Title of host publication	Biomedical Image Registration
Subtitle of host publication	6th International Workshop, WBIR 2014, Proceedings
Editors	Sebastian Ourselin, Marc Modat
Publisher	Springer Verlag
Pages	83-92
Number of pages	10
Volume	8545
ISBN (Electronic)	9783319085548
ISBN (Print)	9783319085531
DOIs	https://doi.org/10.1007/978-3-319-08554-8_9
Publication status	Published - 2014
Externally published	Yes
Event	6th International Workshop on Biomedical Image Registration - London, United Kingdom Duration: 7 Jul 2014 → 8 Jul 2014 Conference number: 6 https://www.springer.com/gp/book/9783319085531

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8545 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	6th International Workshop on Biomedical Image Registration
Abbreviated title	WBIR 2014
Country/Territory	United Kingdom
City	London
Period	7/07/14 → 8/07/14
Internet address	https://www.springer.com/gp/book/9783319085531

Access to Document

10.1007/978-3-319-08554-8_9Licence: Unspecified

Cite this

Carminati, M. C., Piazzese, C., Weinert, L., Tsang, W., Tamborini, G., Pepi, M., Lang, R. M., & Caiani, E. G. (2014). Automated Registration of 3D TEE Datasets of the Descending Aorta for Improved Examination and Quantification of Atheromas Burden. In S. Ourselin, & M. Modat (Eds.), Biomedical Image Registration : 6th International Workshop, WBIR 2014, Proceedings (Vol. 8545, pp. 83-92). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8545 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-08554-8_9

Carminati, M. C. ; Piazzese, C. ; Weinert, L. et al. / Automated Registration of 3D TEE Datasets of the Descending Aorta for Improved Examination and Quantification of Atheromas Burden. Biomedical Image Registration : 6th International Workshop, WBIR 2014, Proceedings. editor / Sebastian Ourselin ; Marc Modat. Vol. 8545 Springer Verlag, 2014. pp. 83-92 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Automated Registration of 3D TEE Datasets of the Descending Aorta for Improved Examination and Quantification of Atheromas Burden",

abstract = "We propose a robust and efficient approach for the reconstruction of the descending aorta from contiguous 3D transesophageal echocardiographic (TEE) images. It is based on an ad hoc protocol, designed to acquire ordered and partially overlapped 3D TEE datasets, followed by automated image registration that relies on this a priori knowledge. The method was validated using artificially derived misaligned images, and then applied to 14 consecutive patients. Both qualitative and quantitative results demonstrated the potential feasibility and accuracy of the proposed approach. Its clinical applicability could improve the assessment of aortic total plaque burden from 3D TEE images.",

keywords = "Transesophageal Echocardiography, Acquisition protocol, Normalize Cross Correlation, Automate registration, Aortic plaque",

author = "Carminati, {M. C.} and C. Piazzese and L. Weinert and W. Tsang and G. Tamborini and M. Pepi and Lang, {R. M.} and Caiani, {E. G.}",

year = "2014",

doi = "10.1007/978-3-319-08554-8_9",

language = "English",

isbn = "9783319085531",

volume = "8545",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "83--92",

editor = "Sebastian Ourselin and Marc Modat",

booktitle = "Biomedical Image Registration",

address = "Germany",

note = "6th International Workshop on Biomedical Image Registration, WBIR 2014 ; Conference date: 07-07-2014 Through 08-07-2014",

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Carminati, MC, Piazzese, C, Weinert, L, Tsang, W, Tamborini, G, Pepi, M, Lang, RM & Caiani, EG 2014, Automated Registration of 3D TEE Datasets of the Descending Aorta for Improved Examination and Quantification of Atheromas Burden. in S Ourselin & M Modat (eds), Biomedical Image Registration : 6th International Workshop, WBIR 2014, Proceedings. vol. 8545, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8545 LNCS, Springer Verlag, pp. 83-92, 6th International Workshop on Biomedical Image Registration, London, United Kingdom, 7/07/14. https://doi.org/10.1007/978-3-319-08554-8_9

Automated Registration of 3D TEE Datasets of the Descending Aorta for Improved Examination and Quantification of Atheromas Burden. / Carminati, M. C.; Piazzese, C.; Weinert, L. et al.

Biomedical Image Registration : 6th International Workshop, WBIR 2014, Proceedings. ed. / Sebastian Ourselin; Marc Modat. Vol. 8545 Springer Verlag, 2014. p. 83-92 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8545 LNCS).

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

TY - GEN

T1 - Automated Registration of 3D TEE Datasets of the Descending Aorta for Improved Examination and Quantification of Atheromas Burden

AU - Carminati, M. C.

AU - Piazzese, C.

AU - Weinert, L.

AU - Tsang, W.

AU - Tamborini, G.

AU - Pepi, M.

AU - Lang, R. M.

AU - Caiani, E. G.

N1 - Conference code: 6

PY - 2014

Y1 - 2014

N2 - We propose a robust and efficient approach for the reconstruction of the descending aorta from contiguous 3D transesophageal echocardiographic (TEE) images. It is based on an ad hoc protocol, designed to acquire ordered and partially overlapped 3D TEE datasets, followed by automated image registration that relies on this a priori knowledge. The method was validated using artificially derived misaligned images, and then applied to 14 consecutive patients. Both qualitative and quantitative results demonstrated the potential feasibility and accuracy of the proposed approach. Its clinical applicability could improve the assessment of aortic total plaque burden from 3D TEE images.

AB - We propose a robust and efficient approach for the reconstruction of the descending aorta from contiguous 3D transesophageal echocardiographic (TEE) images. It is based on an ad hoc protocol, designed to acquire ordered and partially overlapped 3D TEE datasets, followed by automated image registration that relies on this a priori knowledge. The method was validated using artificially derived misaligned images, and then applied to 14 consecutive patients. Both qualitative and quantitative results demonstrated the potential feasibility and accuracy of the proposed approach. Its clinical applicability could improve the assessment of aortic total plaque burden from 3D TEE images.

KW - Transesophageal Echocardiography

KW - Acquisition protocol

KW - Normalize Cross Correlation

KW - Automate registration

KW - Aortic plaque

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U2 - 10.1007/978-3-319-08554-8_9

DO - 10.1007/978-3-319-08554-8_9

M3 - Conference contribution

AN - SCOPUS:84903721280

SN - 9783319085531

VL - 8545

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

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EP - 92

BT - Biomedical Image Registration

A2 - Ourselin, Sebastian

A2 - Modat, Marc

PB - Springer Verlag

T2 - 6th International Workshop on Biomedical Image Registration

Y2 - 7 July 2014 through 8 July 2014

ER -

Carminati MC, Piazzese C, Weinert L, Tsang W, Tamborini G, Pepi M et al. Automated Registration of 3D TEE Datasets of the Descending Aorta for Improved Examination and Quantification of Atheromas Burden. In Ourselin S, Modat M, editors, Biomedical Image Registration : 6th International Workshop, WBIR 2014, Proceedings. Vol. 8545. Springer Verlag. 2014. p. 83-92. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-08554-8_9

Automated Registration of 3D TEE Datasets of the Descending Aorta for Improved Examination and Quantification of Atheromas Burden

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