Fetal cardiac cycle detection in multi-resource echocardiograms using hybrid classification framework

B Pu, N Zhu, K Li, S Li - Future Generation Computer Systems, 2021 - Elsevier
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 …

Cardiac phase detection in echocardiograms with densely gated recurrent neural networks and global extrema loss

FT Dezaki, Z Liao, C Luong, H Girgis… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
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 …

Real-time automatic ejection fraction and foreshortening detection using deep learning

E Smistad, A Østvik, IM Salte… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
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 …

Detection of cardiac events in echocardiography using 3D convolutional recurrent neural networks

AM Fiorito, A Østvik, E Smistad… - 2018 IEEE …, 2018 - ieeexplore.ieee.org
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 …

HFSCCD: a hybrid neural network for fetal standard Cardiac cycle detection in ultrasound videos

B Pu, K Li, J Chen, Y Lu, Q Zeng… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
In the fetal cardiac ultrasound examination, standard cardiac cycle (SCC) recognition is the
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 …

Self-supervised motion descriptor for cardiac phase detection in 4D CMR based on discrete vector field estimations

S Koehler, T Hussain, H Hussain, D Young… - … Workshop on Statistical …, 2022 - Springer
Cardiac magnetic resonance (CMR) sequences visualise the cardiac function voxel-wise
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 …

A deep learning based approach for automatic cardiac events identification

Y Li, K Hong, X Shi, W Pang, Y Xiao, P Zhao… - … Signal Processing and …, 2025 - Elsevier
Abstract Visually identifying End-Diastolic (ED) and End-Systolic (ES) frames from 2D
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) …