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Using deep learning to extract novel and quantitative imaging features from perfluoropropane contrast, sulphur hexafluoride contrast and non-contrast stress echocardiography images

29 August 2020 (08:30 - 08:30)
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Congress Presentation Part of: Novel Technological Approaches in Echocardiography: What Do They Provide? Technology ESC Premium Access ESC Congress 2020

About the speaker

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Mr Cameron Dockerill

King's College London, London (United Kingdom of Great Britain & Northern Ireland)

6 More presentations in this session

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Unsupervised machine learning generated clusters of left ventricular strain curves identifies patients in risk of heart failure and cardiovascular death following acute myocardial infarction
Mr J. Simonsen (Copenhagen, DK)
Abstract Slides
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Artificial intelligence-guided image acquisition on patients with implanted electrophysiological devices: Results from a pivotal prospective multi-center clinical trial
Mr S. Surette (Brisbane, US)
Abstract Slides
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Hemodynamic heterogeneity of inadequate cardiac output increase identified by 2-dimensional volumetric exercise echocardiography: slow, stiff or weak heart?
Doctor T. Bombardini (Banja Luka, BA)
Abstract Slides
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Feasibility, reproducibility, and clinical implications of the fully automated assessment for global longitudinal strain.
Doctor H. Kawakami (Toon, JP)
Abstract Slides
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Fully automated contrast and non-contrast cardiac view detection in echocardiography a multi-centre, multi-vendor study
Doctor A. Beqiri (Oxford, GB)
Abstract Slides

Access the full session

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Novel Technological Approaches in Echocardiography: What Do They Provide?

The Event

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ESC Congress 2020

29 August 2020 08:30 CET
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ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources