AIMC Topic: Heart Ventricles
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Retraining Convolutional Neural Networks for Specialized Cardiovascular Imaging Tasks: Lessons from Tetralogy of Fallot.
Pediatric cardiology
Jan 4, 2021
Ventricular contouring of cardiac magnetic resonance imaging is the gold standard for volumetric analysis for repaired tetralogy of Fallot (rTOF), but can be time-consuming and subject to variability. A convolutional neural network (CNN) ventricular ...
Comparative analysis of active contour and convolutional neural network in rapid left-ventricle volume quantification using echocardiographic imaging.
Computer methods and programs in biomedicine
Dec 17, 2020
In cardiology, ultrasound is often used to diagnose heart disease associated with myocardial infarction. This study aims to develop robust segmentation techniques for segmenting the left ventricle (LV) in ultrasound images to check myocardium movemen...
Diagnosis and risk stratification in hypertrophic cardiomyopathy using machine learning wall thickness measurement: a comparison with human test-retest performance.
The Lancet. Digital health
Dec 3, 2020
BACKGROUND: Left ventricular maximum wall thickness (MWT) is central to diagnosis and risk stratification of hypertrophic cardiomyopathy, but human measurement is prone to variability. We developed an automated machine learning algorithm for MWT meas...
LU-Net: A Multistage Attention Network to Improve the Robustness of Segmentation of Left Ventricular Structures in 2-D Echocardiography.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 24, 2020
Segmentation of cardiac structures is one of the fundamental steps to estimate volumetric indices of the heart. This step is still performed semiautomatically in clinical routine and is, thus, prone to interobserver and intraobserver variabilities. R...
Real-Time Automatic Ejection Fraction and Foreshortening Detection Using Deep Learning.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 24, 2020
Volume and ejection fraction (EF) measurements of the left ventricle (LV) in 2-D echocardiography are associated with a high uncertainty not only due to interobserver variability of the manual measurement, but also due to ultrasound acquisition error...
Evaluation of a delineation software for cardiac atlas-based autosegmentation: An example of the use of artificial intelligence in modern radiotherapy.
Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Nov 2, 2020
PURPOSE: The primary objective of this work was to implement and evaluate a cardiac atlas-based autosegmentation technique based on the "Workflow Box" software (Mirada Medical, Oxford UK), in order to delineate cardiac substructures according to Euro...
Simulator-generated training datasets as an alternative to using patient data for machine learning: An example in myocardial segmentation with MRI.
Computer methods and programs in biomedicine
Oct 27, 2020
BACKGROUND AND OBJECTIVE: Supervised Machine Learning techniques have shown significant potential in medical image analysis. However, the training data that need to be collected for these techniques in the field of MRI 1) may not be available, 2) may...
Machine Learning Outcome Prediction in Dilated Cardiomyopathy Using Regional Left Ventricular Multiparametric Strain.
Annals of biomedical engineering
Oct 1, 2020
The clinical presentation of idiopathic dilated cardiomyopathy (IDCM) heart failure (HF) patients who will respond to medical therapy (responders) and those who will not (non-responders) is often similar. A machine learning (ML)-based clinical tool t...
Diagnosis of left ventricular hypertrophy using convolutional neural network.
BMC medical informatics and decision making
Sep 25, 2020
BACKGROUND: Clinically, doctors obtain the left ventricular posterior wall thickness (LVPWT) mainly by observing ultrasonic echocardiographic video stream to capture a single frame of images with diagnostic significance, and then mark two key points ...
A novel solution of using deep learning for left ventricle detection: Enhanced feature extraction.
Computer methods and programs in biomedicine
Sep 15, 2020
BACKGROUND AND AIM: deep learning algorithms have not been successfully used for the left ventricle (LV) detection in echocardiographic images due to overfitting and vanishing gradient descent problem. This research aims to increase accuracy and impr...
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