Automated cardiovascular magnetic resonance image analysis with fully convolutional networks

Automated cardiovascular magnetic resonance image analysis with fully convolutional networks

Abstract Background Cardiovascular resonance (CMR) imaging is a standard imaging modality for assessing cardiovascular diseases (CVDs), the leading cause of death globally. CMR enables accurate quantification of the cardiac chamber volume, ejection fraction and myocardial mass, providing information...

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Bibliographic Details
Main Authors: Wenjia Bai, Matthew Sinclair, Giacomo Tarroni, Ozan Oktay, Martin Rajchl, Ghislain Vaillant, Aaron M. Lee, Nay Aung, Elena Lukaschuk, Mihir M. Sanghvi, Filip Zemrak, Kenneth Fung, Jose Miguel Paiva, Valentina Carapella, Young Jin Kim, Hideaki Suzuki, Bernhard Kainz, Paul M. Matthews, Steffen E. Petersen, Stefan K. Piechnik, Stefan Neubauer, Ben Glocker, Daniel Rueckert
Format: Article
Language:English
Published: Elsevier 2018-09-01
Series:Journal of Cardiovascular Magnetic Resonance
Subjects:
CMR image analysis
Fully convolutional networks
Machine learning
Online Access:http://link.springer.com/article/10.1186/s12968-018-0471-x

Internet

http://link.springer.com/article/10.1186/s12968-018-0471-x

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