AIMC Topic: Heart Ventricles
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Machine learning-based phenogrouping in heart failure to identify responders to cardiac resynchronization therapy.
European journal of heart failure
Oct 17, 2018
AIMS: We tested the hypothesis that a machine learning (ML) algorithm utilizing both complex echocardiographic data and clinical parameters could be used to phenogroup a heart failure (HF) cohort and identify patients with beneficial response to card...
Deep Learning for Cardiac MRI: The Time Has Come.
Radiology
Oct 9, 2018
Deep Learning-based Method for Fully Automatic Quantification of Left Ventricle Function from Cine MR Images: A Multivendor, Multicenter Study.
Radiology
Oct 9, 2018
Purpose To develop a deep learning-based method for fully automated quantification of left ventricular (LV) function from short-axis cine MR images and to evaluate its performance in a multivendor and multicenter setting. Materials and Methods This r...
Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Sep 27, 2018
Combined analysis of SPECT myocardial perfusion imaging (MPI) performed with a solid-state camera on patients in 2 positions (semiupright, supine) is routinely used to mitigate attenuation artifacts. We evaluated the prediction of obstructive disease...
Multi-dimensional proprio-proximus machine learning for assessment of myocardial infarction.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Sep 26, 2018
This work presents a novel analysis methodology that utilises high-resolution, multi-dimensional information to better classify regions of the left ventricle after myocardial infarction. Specifically, the focus is to determine degree of infarction in...
Diagnosis of Heart Failure With Preserved Ejection Fraction: Machine Learning of Spatiotemporal Variations in Left Ventricular Deformation.
Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Aug 23, 2018
BACKGROUND: Stress testing helps diagnose heart failure with preserved ejection fraction (HFpEF), but there are no established criteria for quantifying left ventricular (LV) functional reserve. The aim of this study was to investigate whether compreh...
Neural multi-atlas label fusion: Application to cardiac MR images.
Medical image analysis
Jul 31, 2018
Multi-atlas segmentation approach is one of the most widely-used image segmentation techniques in biomedical applications. There are two major challenges in this category of methods, i.e., atlas selection and label fusion. In this paper, we propose a...
Phenotypic Clustering of Left Ventricular Diastolic Function Parameters: Patterns and Prognostic Relevance.
JACC. Cardiovascular imaging
Apr 18, 2018
OBJECTIVES: This study sought to explore the natural clustering of echocardiographic variables used for assessing left ventricular (LV) diastolic dysfunction (DD) in order to isolate high-risk phenotypic patterns and assess their prognostic significa...
Cluster Analysis
Predictive Value of Tests
Cause of Death
Retrospective Studies
Humans
Heart Ventricles
Ventricular Function, Left
Echocardiography, Doppler, Pulsed
Female
Machine Learning
Aged
Middle Aged
Progression-Free Survival
Risk Factors
Phenotype
Aged, 80 and over
Risk Assessment
Ventricular Dysfunction, Left
Pattern Recognition, Automated
Hospitalization
Male
Disease Progression
Image Interpretation, Computer-Assisted
Diastole
Echocardiography, Doppler, Color
3-D Consistent and Robust Segmentation of Cardiac Images by Deep Learning With Spatial Propagation.
IEEE transactions on medical imaging
Mar 29, 2018
We propose a method based on deep learning to perform cardiac segmentation on short axis Magnetic resonance imaging stacks iteratively from the top slice (around the base) to the bottom slice (around the apex). At each iteration, a novel variant of t...
Effects of Transcatheter Mitral Valve Repair With MitraClip on Left Ventricular and Atrial Hemodynamic Load and Myocardial Wall Stress.
Journal of cardiac failure
Dec 29, 2017
AIMS: To evaluate the effects of MitraClip on left ventricular (LV) and left atrial (LA) myocardial wall stress as assessed with the use of N-terminal pro-B-type natriuretic peptide (NT-proBNP) and strain imaging.
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