Regional Multi-View Learning for Cardiac Motion Analysis: Application to Identification of Dilated Cardiomyopathy Patients.

Journal: IEEE transactions on bio-medical engineering

Published Date: Aug 15, 2018

Abstract

OBJECTIVE: The aim of this paper is to describe an automated diagnostic pipeline that uses as input only ultrasound (US) data, but is at the same time informed by a training database of multimodal magnetic resonance (MR) and US image data.

Authors

Esther Puyol-Anton
Bram Ruijsink
Bernhard Gerber
Mihaela Silvia Amzulescu
Helene Langet
Mathieu De Craene

Philips Research France, 92150 Suresnes, France.
Julia A Schnabel

Division of Imaging Sciences and Biomedical Engineering, King's College London, UK.
Paolo Piro
Andrew P King

Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom. Electronic address: andrew.king@kcl.ac.uk.

Keywords

Algorithms Cardiomyopathy, Dilated Databases, Factual Heart Humans Image Interpretation, Computer-Assisted Machine Learning Magnetic Resonance Imaging Movement Multimodal Imaging Support Vector Machine Ultrasonography

External Resources

View on PubMed Access via DOI PubMed (30113891)

Regional Multi-View Learning for Cardiac Motion Analysis: Application to Identification of Dilated Cardiomyopathy Patients.

Abstract

Authors

Keywords

External Resources

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