Fetal cardiac cycle detection in multi-resource echocardiograms using hybrid classification framework
Accurate acquisition of end-systolic (ES) and end-diastolic (ED) frames from ultrasound
videos of fetal echocardiograms is a key procedure in the automated biometric …
videos of fetal echocardiograms is a key procedure in the automated biometric …
Cardiac phase detection in echocardiograms with densely gated recurrent neural networks and global extrema loss
Accurate detection of end-systolic (ES) and end-diastolic (ED) frames in an
echocardiographic cine series can be difficult but necessary pre-processing step for the …
echocardiographic cine series can be difficult but necessary pre-processing step for the …
Real-time automatic ejection fraction and foreshortening detection using deep learning
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 …
echocardiography are associated with a high uncertainty not only due to interobserver …
Detection of cardiac events in echocardiography using 3D convolutional recurrent neural networks
A proper definition of cardiac events such as end-diastole (ED) and end-systole (ES) is
important for quantitative measurements in echocardiography. While ED can be found using …
important for quantitative measurements in echocardiography. While ED can be found using …
HFSCCD: a hybrid neural network for fetal standard Cardiac cycle detection in ultrasound videos
In the fetal cardiac ultrasound examination, standard cardiac cycle (SCC) recognition is the
essential foundation for diagnosing congenital heart disease. Previous studies have mostly …
essential foundation for diagnosing congenital heart disease. Previous studies have mostly …
Semi-supervised learning improves the performance of cardiac event detection in echocardiography
Y Li, H Li, F Wu, J Luo - Ultrasonics, 2023 - Elsevier
Detection of end-diastole (ED) and end-systole (ES) frames in echocardiography video is a
critical step for assessment of cardiac function. A recently released large public dataset, ie …
critical step for assessment of cardiac function. A recently released large public dataset, ie …
Self-supervised motion descriptor for cardiac phase detection in 4D CMR based on discrete vector field estimations
Cardiac magnetic resonance (CMR) sequences visualise the cardiac function voxel-wise
over time. Simultaneously, deep learning-based deformable image registration is able to …
over time. Simultaneously, deep learning-based deformable image registration is able to …
Automatic detection of end‐diastolic and end‐systolic frames in 2D echocardiography
M Zolgharni, M Negoita, NM Dhutia… - …, 2017 - Wiley Online Library
Background Correctly selecting the end‐diastolic and end‐systolic frames on a 2D
echocardiogram is important and challenging, for both human experts and automated …
echocardiogram is important and challenging, for both human experts and automated …
A deep learning based approach for automatic cardiac events identification
Abstract Visually identifying End-Diastolic (ED) and End-Systolic (ES) frames from 2D
echocardiographic videos without electrocardiogram is time-consuming but a fundamental …
echocardiographic videos without electrocardiogram is time-consuming but a fundamental …
Machine learning for cardiac ultrasound time series data
B Yuan, SR Chitturi, G Iyer, N Li, X Xu… - Medical imaging …, 2017 - spiedigitallibrary.org
We consider the problem of identifying frames in a cardiac ultrasound video associated with
left ventricular chamber end-systolic (ES, contraction) and end-diastolic (ED, expansion) …
left ventricular chamber end-systolic (ES, contraction) and end-diastolic (ED, expansion) …