[HTML][HTML] Constrained transformer network for ECG signal processing and arrhythmia classification
Background Heart disease diagnosis is a challenging task and it is important to explore
useful information from the massive amount of electrocardiogram (ECG) records of patients …
useful information from the massive amount of electrocardiogram (ECG) records of patients …
Automated characterization of the fetal heart in ultrasound images using fully convolutional neural networks
Automatic analysis of fetal echocardiography screening images could aid in the
identification of congenital heart diseases. The first step towards automatic fetal …
identification of congenital heart diseases. The first step towards automatic fetal …
[HTML][HTML] EchoEFNet: multi-task deep learning network for automatic calculation of left ventricular ejection fraction in 2D echocardiography
H Li, Y Wang, M Qu, P Cao, C Feng, J Yang - Computers in Biology and …, 2023 - Elsevier
Left ventricular ejection fraction (LVEF) is essential for evaluating left ventricular systolic
function. However, its clinical calculation requires the physician to interactively segment the …
function. However, its clinical calculation requires the physician to interactively segment the …
Cardio Twin: A Digital Twin of the human heart running on the edge
R Martinez-Velazquez, R Gamez… - 2019 IEEE international …, 2019 - ieeexplore.ieee.org
We present the Cardio Twin architecture for Ischemic Heart Disease (IHD) detection
designed to run on the edge. We classify non-myocardial and myocardial conditions with a …
designed to run on the edge. We classify non-myocardial and myocardial conditions with a …
CardioXNet: A novel lightweight deep learning framework for cardiovascular disease classification using heart sound recordings
The alarmingly high mortality rate and increasing global prevalence of cardiovascular
diseases (CVDs) signify the crucial need for early detection schemes. Phonocardiogram …
diseases (CVDs) signify the crucial need for early detection schemes. Phonocardiogram …
IFT-net: Interactive fusion transformer network for quantitative analysis of pediatric echocardiography
The task of automatic segmentation and measurement of key anatomical structures in
echocardiography is critical for subsequent extraction of clinical parameters. However, the …
echocardiography is critical for subsequent extraction of clinical parameters. However, the …
Assessment and validation of a novel fast fully automated artificial intelligence left ventricular ejection fraction quantification software
R Samtani, S Bienstock, AC Lai, S Liao… - …, 2022 - Wiley Online Library
Background Quantification of left ventricular ejection fraction (LVEF) by transthoracic
echocardiography (TTE) is operator‐dependent, time‐consuming, and error‐prone. LVivoEF …
echocardiography (TTE) is operator‐dependent, time‐consuming, and error‐prone. LVivoEF …
[HTML][HTML] A wearable cardiac ultrasound imager
Continuous imaging of cardiac functions is highly desirable for the assessment of long-term
cardiovascular health, detection of acute cardiac dysfunction and clinical management of …
cardiovascular health, detection of acute cardiac dysfunction and clinical management of …
A computer vision pipeline for automated determination of cardiac structure and function and detection of disease by two-dimensional echocardiography
Automated cardiac image interpretation has the potential to transform clinical practice in
multiple ways including enabling low-cost serial assessment of cardiac function in the …
multiple ways including enabling low-cost serial assessment of cardiac function in the …
Myocardial function imaging in echocardiography using deep learning
Deformation imaging in echocardiography has been shown to have better diagnostic and
prognostic value than conventional anatomical measures such as ejection fraction …
prognostic value than conventional anatomical measures such as ejection fraction …