Learning a global descriptor of cardiac motion from a large cohort of 1000+ normal subjects

Wenjia Bai; Devis Peressutti; Ozan Oktay; Wenzhe Shi; Declan P. O’Regan; Andrew P. King; Daniel Rueckert

doi:10.1007/978-3-319-20309-6_1

Learning a global descriptor of cardiac motion from a large cohort of 1000+ normal subjects

Wenjia Bai, Devis Peressutti, Ozan Oktay, Wenzhe Shi, Declan P. O’Regan, Andrew P. King, Daniel Rueckert

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

2 Scopus citations

Abstract

Motion, together with shape, reflect important aspects of cardiac function. In this work, a new method is proposed for learning of a cardiac motion descriptor from a data-driven perspective. The resulting descriptor can characterise the global motion pattern of the left ventricle with a much lower dimension than the original motion data. It has demonstrated its predictive power on two exemplar classification tasks on a large cohort of 1093 normal subjects.

Original language	English
Title of host publication	Functional Imaging and Modeling of the Heart - 8th International Conference, FIMH 2015, Proceedings
Editors	Hans van Assen, Peter Bovendeerd, Hans van Assen, Peter Bovendeerd, Tammo Delhaas, Tammo Delhaas
Publisher	Springer Verlag
Pages	3-11
Number of pages	9
ISBN (Print)	9783319203089, 9783319203089
DOIs	https://doi.org/10.1007/978-3-319-20309-6_1
State	Published - 2015
Externally published	Yes
Event	8th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2015 - Maastricht, Netherlands Duration: 25 Jun 2015 → 27 Jun 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9126
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2015
Country/Territory	Netherlands
City	Maastricht
Period	25/06/15 → 27/06/15

Access to Document

10.1007/978-3-319-20309-6_1

Cite this

Bai, W., Peressutti, D., Oktay, O., Shi, W., O’Regan, D. P., King, A. P., & Rueckert, D. (2015). Learning a global descriptor of cardiac motion from a large cohort of 1000+ normal subjects. In H. van Assen, P. Bovendeerd, H. van Assen, P. Bovendeerd, T. Delhaas, & T. Delhaas (Eds.), Functional Imaging and Modeling of the Heart - 8th International Conference, FIMH 2015, Proceedings (pp. 3-11). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9126). Springer Verlag. https://doi.org/10.1007/978-3-319-20309-6_1

Bai, Wenjia ; Peressutti, Devis ; Oktay, Ozan et al. / Learning a global descriptor of cardiac motion from a large cohort of 1000+ normal subjects. Functional Imaging and Modeling of the Heart - 8th International Conference, FIMH 2015, Proceedings. editor / Hans van Assen ; Peter Bovendeerd ; Hans van Assen ; Peter Bovendeerd ; Tammo Delhaas ; Tammo Delhaas. Springer Verlag, 2015. pp. 3-11 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Motion, together with shape, reflect important aspects of cardiac function. In this work, a new method is proposed for learning of a cardiac motion descriptor from a data-driven perspective. The resulting descriptor can characterise the global motion pattern of the left ventricle with a much lower dimension than the original motion data. It has demonstrated its predictive power on two exemplar classification tasks on a large cohort of 1093 normal subjects.",

author = "Wenjia Bai and Devis Peressutti and Ozan Oktay and Wenzhe Shi and O{\textquoteright}Regan, {Declan P.} and King, {Andrew P.} and Daniel Rueckert",

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year = "2015",

doi = "10.1007/978-3-319-20309-6_1",

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

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Bai, W, Peressutti, D, Oktay, O, Shi, W, O’Regan, DP, King, AP & Rueckert, D 2015, Learning a global descriptor of cardiac motion from a large cohort of 1000+ normal subjects. in H van Assen, P Bovendeerd, H van Assen, P Bovendeerd, T Delhaas & T Delhaas (eds), Functional Imaging and Modeling of the Heart - 8th International Conference, FIMH 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9126, Springer Verlag, pp. 3-11, 8th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2015, Maastricht, Netherlands, 25/06/15. https://doi.org/10.1007/978-3-319-20309-6_1

Learning a global descriptor of cardiac motion from a large cohort of 1000+ normal subjects. / Bai, Wenjia; Peressutti, Devis; Oktay, Ozan et al.
Functional Imaging and Modeling of the Heart - 8th International Conference, FIMH 2015, Proceedings. ed. / Hans van Assen; Peter Bovendeerd; Hans van Assen; Peter Bovendeerd; Tammo Delhaas; Tammo Delhaas. Springer Verlag, 2015. p. 3-11 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9126).

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

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AU - O’Regan, Declan P.

AU - King, Andrew P.

AU - Rueckert, Daniel

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AB - Motion, together with shape, reflect important aspects of cardiac function. In this work, a new method is proposed for learning of a cardiac motion descriptor from a data-driven perspective. The resulting descriptor can characterise the global motion pattern of the left ventricle with a much lower dimension than the original motion data. It has demonstrated its predictive power on two exemplar classification tasks on a large cohort of 1093 normal subjects.

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Bai W, Peressutti D, Oktay O, Shi W, O’Regan DP, King AP et al. Learning a global descriptor of cardiac motion from a large cohort of 1000+ normal subjects. In van Assen H, Bovendeerd P, van Assen H, Bovendeerd P, Delhaas T, Delhaas T, editors, Functional Imaging and Modeling of the Heart - 8th International Conference, FIMH 2015, Proceedings. Springer Verlag. 2015. p. 3-11. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-20309-6_1

Learning a global descriptor of cardiac motion from a large cohort of 1000+ normal subjects

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