Ultrasound video transformers for cardiac ejection fraction estimation
Cardiac ultrasound imaging is used to diagnose various heart diseases. Common analysis
pipelines involve manual processing of the video frames by expert clinicians. This suffers …
pipelines involve manual processing of the video frames by expert clinicians. This suffers …
EchoCoTr: Estimation of the left ventricular ejection fraction from spatiotemporal echocardiography
R Muhtaseb, M Yaqub - … Conference on Medical Image Computing and …, 2022 - Springer
Learning spatiotemporal features is an important task for efficient video understanding
especially in medical images such as echocardiograms. Convolutional neural networks …
especially in medical images such as echocardiograms. Convolutional neural networks …
Automatic biplane left ventricular ejection fraction estimation with mobile point-of-care ultrasound using multi-task learning and adversarial training
Purpose Left ventricular ejection fraction (LVEF) is one of the key metrics to assess the heart
functionality, and cardiac ultrasound (echo) is a standard imaging modality for EF …
functionality, and cardiac ultrasound (echo) is a standard imaging modality for EF …
A deep Bayesian video analysis framework: towards a more robust estimation of ejection fraction
MM Kazemi Esfeh, C Luong, D Behnami… - … Conference on Medical …, 2020 - Springer
Ejection Fraction (EF) is a widely-used and critical index of cardiac health. EF measures the
efficacy of the cyclic contraction of the ventricles and the outward pumpage of blood through …
efficacy of the cyclic contraction of the ventricles and the outward pumpage of blood through …
Explicit and automatic ejection fraction assessment on 2D cardiac ultrasound with a deep learning-based approach
O Moal, E Roger, A Lamouroux, C Younes… - Computers in biology …, 2022 - Elsevier
Background Ejection fraction (EF) is a key parameter for assessing cardiovascular functions
in cardiac ultrasound, but its manual assessment is time-consuming and subject to high inter …
in cardiac ultrasound, but its manual assessment is time-consuming and subject to high inter …
Fully automatic real-time ejection fraction and MAPSE measurements in 2D echocardiography using deep neural networks
Cardiac ultrasound measurements such as left ventricular volume, ejection fraction (EF) and
mitral annular plane systolic excursion (MAPSE) are time consuming and highly observer …
mitral annular plane systolic excursion (MAPSE) are time consuming and highly observer …
Video-based AI for beat-to-beat assessment of cardiac function
Accurate assessment of cardiac function is crucial for the diagnosis of cardiovascular
disease, screening for cardiotoxicity and decisions regarding the clinical management of …
disease, screening for cardiotoxicity and decisions regarding the clinical management of …
Recognizing end-diastole and end-systole frames via deep temporal regression network
Accurate measurement of left ventricular volumes and Ejection Fraction from cine MRI is of
paramount importance to the evaluation of cardiovascular functions, yet it usually requires …
paramount importance to the evaluation of cardiovascular functions, yet it usually requires …
[HTML][HTML] A foundational vision transformer improves diagnostic performance for electrocardiograms
The electrocardiogram (ECG) is a ubiquitous diagnostic modality. Convolutional neural
networks (CNNs) applied towards ECG analysis require large sample sizes, and transfer …
networks (CNNs) applied towards ECG analysis require large sample sizes, and transfer …
Bat: Beat-aligned transformer for electrocardiogram classification
X Li, C Li, Y Wei, Y Sun, J Wei, X Li… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Electrocardiogram (ECG) is one of the critical diagnostic tools in healthcare. Various deep
learning models, except Transformers, have been explored and applied to map ECG …
learning models, except Transformers, have been explored and applied to map ECG …