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

Bai W, Peressutti D, Oktay O, Shi W, O'Regan DP, King AP, Rueckert D (2015)

Publication Type: Conference contribution

Publication year: 2015

Journal

Lecture Notes in Computer Science Springer Verlag

Publisher: Springer Verlag

Book Volume: 9126

Pages Range: 3-11

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: Maastricht, NLD

ISBN: 9783319203089

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

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.

Involved external institutions

Imperial College London / The Imperial College of Science, Technology and Medicine GB United Kingdom (GB) King’s College London GB United Kingdom (GB)

How to cite

APA:

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 Hans van Assen, Peter Bovendeerd, Hans van Assen, Peter Bovendeerd, Tammo Delhaas, Tammo Delhaas (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 3-11). Maastricht, NLD: Springer Verlag.

MLA:

Bai, Wenjia, et al. "Learning a global descriptor of cardiac motion from a large cohort of 1000+ normal subjects." Proceedings of the 8th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2015, Maastricht, NLD Ed. Hans van Assen, Peter Bovendeerd, Hans van Assen, Peter Bovendeerd, Tammo Delhaas, Tammo Delhaas, Springer Verlag, 2015. 3-11.

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