Deep learning has become the most widely used approach for cardiac image segmentation
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …

The renaissance of deep learning has provided promising solutions to various tasks. While
conventional deep learning models are constructed for a single specific task, multi-task deep …

Echocardiography (Echo), a widely available, noninvasive, and portable bedside imaging
tool, is the most frequently used imaging modality in assessing cardiac anatomy and …

Imaging plays a fundamental role in the effective diagnosis, staging, management, and
monitoring of various cardiac pathologies. Successful radiological analysis relies on …

Abstract Machine learning promises to assist physicians with predictions of mortality and of
other future clinical events by learning complex patterns from historical data, such as …

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 …

Accurate estimation of ejection fraction (EF) from echocardiography is of great importance
for evaluation of cardiac function. It is usually obtained by the Simpson's bi-plane method …

The integration of segmentation and direct quantification on the left ventricle (LV) from the
paired apical views (ie, apical 4-chamber and 2-chamber together) echo sequence clinically …

Aims Echocardiography is a cornerstone in cardiac imaging, and left ventricular (LV)
ejection fraction (EF) is a key parameter for patient management. Recent advances in …

The echocardiogram is a test that is widely used in Heart Disease Diagnoses. However, its
analysis is largely dependent on the physician's experience. In this regard, artificial …