AIMC Topic: Ventricular Function, Left

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A new method incorporating deep learning with shape priors for left ventricular segmentation in myocardial perfusion SPECT images.

Computers in biology and medicine
Accurate segmentation of the left ventricle (LV) is crucial for evaluating myocardial perfusion SPECT (MPS) and assessing LV functions. In this study, a novel method combining deep learning with shape priors was developed and validated to extract the...

Blinded, randomized trial of sonographer versus AI cardiac function assessment.

Nature
Artificial intelligence (AI) has been developed for echocardiography, although it has not yet been tested with blinding and randomization. Here we designed a blinded, randomized non-inferiority clinical trial (ClinicalTrials.gov ID: NCT05140642; no o...

Deep Learning for Improved Precision and Reproducibility of Left Ventricular Strain in Echocardiography: A Test-Retest Study.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
AIMS: Assessment of left ventricular (LV) function by echocardiography is hampered by modest test-retest reproducibility. A novel artificial intelligence (AI) method based on deep learning provides fully automated measurements of LV global longitudin...

EchoEFNet: Multi-task deep learning network for automatic calculation of left ventricular ejection fraction in 2D echocardiography.

Computers in biology and medicine
Left ventricular ejection fraction (LVEF) is essential for evaluating left ventricular systolic function. However, its clinical calculation requires the physician to interactively segment the left ventricle and obtain the mitral annulus and apical la...

Video-Based Deep Learning for Automated Assessment of Left Ventricular Ejection Fraction in Pediatric Patients.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
BACKGROUND: Significant interobserver and interstudy variability occurs for left ventricular (LV) functional indices despite standardization of measurement techniques. Artificial intelligence models trained on adult echocardiograms are not likely to ...

A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram.

Nature communications
This study compares a deep learning interpretation of 23 echocardiographic parameters-including cardiac volumes, ejection fraction, and Doppler measurements-with three repeated measurements by core lab sonographers. The primary outcome metric, the in...

Machine Learning-Enabled Fully Automated Assessment of Left Ventricular Volume, Ejection Fraction and Strain: Experience in Pediatric and Young Adult Echocardiography.

Pediatric cardiology
BACKGROUND: Left ventricular (LV) volumes, ejection fraction (EF), and myocardial strain have been shown to be predictive of clinical and subclinical heart disease. Automation of LV functional assessment overcomes difficult technical challenges and c...

Deep learning of ECG waveforms for diagnosis of heart failure with a reduced left ventricular ejection fraction.

Scientific reports
The performance and clinical implications of the deep learning aided algorithm using electrocardiogram of heart failure (HF) with reduced ejection fraction (DeepECG-HFrEF) were evaluated in patients with acute HF. The DeepECG-HFrEF algorithm was trai...

Revealing Unforeseen Diagnostic Image Features With Deep Learning by Detecting Cardiovascular Diseases From Apical 4-Chamber Ultrasounds.

Journal of the American Heart Association
Background With the increase of highly portable, wireless, and low-cost ultrasound devices and automatic ultrasound acquisition techniques, an automated interpretation method requiring only a limited set of views as input could make preliminary cardi...

A method using deep learning to discover new predictors from left-ventricular mechanical dyssynchrony for CRT response.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: Studies have shown that the conventional parameters characterizing left ventricular mechanical dyssynchrony (LVMD) measured on gated SPECT myocardial perfusion imaging (MPI) have their own statistical limitations in predicting cardiac res...