Using Machine Learning to Identify Noninvasive Motion-Based Biomarkers of Cardiac Function
Lead Research Organisation:
Imperial College London
Department Name: Computing
Abstract
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Organisations
Publications
Bai W
(2015)
Multi-atlas segmentation with augmented features for cardiac MR images.
in Medical image analysis
Bai W
(2015)
A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion.
in Medical image analysis
Bernard O
(2016)
Standardized Evaluation System for Left Ventricular Segmentation Algorithms in 3D Echocardiography.
in IEEE transactions on medical imaging
Corden B
(2016)
Relationship between body composition and left ventricular geometry using three dimensional cardiovascular magnetic resonance.
in Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Curran L
(2023)
Genotype-Phenotype Taxonomy of Hypertrophic Cardiomyopathy
in Circulation: Genomic and Precision Medicine
De Marvao A
(2015)
Precursors of Hypertensive Heart Phenotype Develop in Healthy Adults: A High-Resolution 3D MRI Study.
in JACC. Cardiovascular imaging
Description | In this project we have developed a number of new machine learning techniques for the interpretation of cardiac MR images. These techniques can be used to automatically extract quantitative information about the cardiovascular system from MR images. In particular, we have developed algorithms for the automatic segmentation of the heart (left and right ventricle as well as myocardium) and the automated tracking of the heart. In addition, the project has developed techniques for the construction of an atlas of the structure and function of the heart. |
Exploitation Route | In future, the developed algorithms may be adopted by the medical imaging industry to support automatic interpretation of cardiac MR images. |
Sectors | Healthcare |
URL | https://biomedia.doc.ic.ac.uk/project/using-machine-learning-to-identify-noninvasive-motion-based-biomarkers-of-cardiac-function/ |
Description | SmartHeart: Next-generation cardiovascular healthcare via integrated image acquisition, reconstruction, analysis and learning. |
Amount | £5,127,775 (GBP) |
Funding ID | EP/P001009/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 09/2016 |
End | 09/2021 |