This study extends the state of the art of deep learning convolutional neural network (CNN)
to the classification of video images of echocardiography, aiming at assisting clinicians in …

Transthoracic echocardiography (echo) is the most common imaging modality for diagnosis
of cardiac conditions. Echo is acquired from a multitude of views, each of which distinctly …

Echocardiography is essential to cardiology. However, the need for human interpretation
has limited echocardiography's full potential for precision medicine. Deep learning is an …

Echocardiography is the commonest medical ultrasound examination, but automated
interpretation is challenging and hinges on correct recognition of the 'view'(imaging plane …

Transthoracic echocardiography examinations are usually performed according to a
protocol comprising different probe postures providing standard views of the heart. These …

A proper echocardiographic study requires several video clips recorded from different
acquisition angles for observation of the complex cardiac anatomy. However, these video …

Abstract Machine learning analysis of biomedical images has seen significant recent
advances. In contrast, there has been much less work on medical videos, despite the fact …

Deep learning and computer vision algorithms can deliver highly accurate and automated
interpretation of medical imaging to augment and assist clinicians. However, medical …

Echocardiography (echo) is an ultrasound imaging modality that is widely used for various
cardiovascular diagnosis tasks. Due to inter-observer variability in echo-based diagnosis …

This article experiments with deep learning methodologies in echocardiogram (echo), a
promising and vigorously researched technique in the preponderance field. This paper …