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Multiview machine learning using an atlas of cardiac cycle motion

Puyol-Anton E, Sinclair M, Gerber B, Amzulescu MS, Langet H, De Craene M, Aljabar P, Schnabel JA, Piro P, King AP (2018)

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Publication Type: Conference contribution

Publication year: 2018

Journal

Publisher: Springer Verlag

Book Volume: 10663 LNCS

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: Quebec City, QC, CAN

ISBN: 9783319755403

DOI: 10.1007/978-3-319-75541-0_1

Abstract

A cardiac motion atlas provides a space of reference in which the cardiac motion fields of a cohort of subjects can be directly compared. From such atlases, descriptors can be learned for subsequent diagnosis and characterization of disease. Traditionally, such atlases have been formed from imaging data acquired using a single modality. In this work we propose a framework for building a multimodal cardiac motion atlas from MR and ultrasound data and incorporate a multiview classifier to exploit the complementary information provided by the two modalities. We demonstrate that our novel framework is able to detect non ischemic dilated cardiomyopathy patients from ultrasound data alone, whilst still exploiting the MR based information from the multimodal atlas. We evaluate two different approaches based on multiview learning to implement the classifier and achieve an improvement in classification performance from 77.5% to 83.50% compared to the use of US data without the multimodal atlas.

Involved external institutions

How to cite

APA:

Puyol-Anton, E., Sinclair, M., Gerber, B., Amzulescu, M.S., Langet, H., De Craene, M.,... King, A.P. (2018). Multiview machine learning using an atlas of cardiac cycle motion. In Olivier Bernard, Pierre-Marc Jodoin, Xiahai Zhuang, Guang Yang, Alistair Young, Maxime Sermesant, Alain Lalande, Mihaela Pop (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 3-11). Quebec City, QC, CAN: Springer Verlag.

MLA:

Puyol-Anton, Esther, et al. "Multiview machine learning using an atlas of cardiac cycle motion." Proceedings of the 8th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, CAN Ed. Olivier Bernard, Pierre-Marc Jodoin, Xiahai Zhuang, Guang Yang, Alistair Young, Maxime Sermesant, Alain Lalande, Mihaela Pop, Springer Verlag, 2018. 3-11.

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