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Heart

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Automatic multi-view pose estimation in focused cardiac ultrasound.

Medical image analysis
Focused cardiac ultrasound (FoCUS) is a valuable point-of-care method for evaluating cardiovascular structures and function, but its scope is limited by equipment and operator's experience, resulting in primarily qualitative 2D exams. This study pres...

Segmentation-based cardiomegaly detection based on semi-supervised estimation of cardiothoracic ratio.

Scientific reports
The successful integration of neural networks in a clinical setting is still uncommon despite major successes achieved by artificial intelligence in other domains. This is mainly due to the black box characteristic of most optimized models and the un...

Circadian assessment of heart failure using explainable deep learning and novel multi-parameter polar images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Heart failure (HF) is a multi-faceted and life-threatening syndrome that affects more than 64.3 million people worldwide. Current gold-standard screening technique, echocardiography, neglects cardiovascular information regul...

Deep learning-based prediction of major arrhythmic events in dilated cardiomyopathy: A proof of concept study.

PloS one
Prediction of major arrhythmic events (MAEs) in dilated cardiomyopathy represents an unmet clinical goal. Computational models and artificial intelligence (AI) are new technological tools that could offer a significant improvement in our ability to p...

A Deep Learning-Based Integrated Framework for Quality-Aware Undersampled Cine Cardiac MRI Reconstruction and Analysis.

IEEE transactions on bio-medical engineering
Cine cardiac magnetic resonance (CMR) imaging is considered the gold standard for cardiac function evaluation. However, cine CMR acquisition is inherently slow and in recent decades considerable effort has been put into accelerating scan times withou...

Overview and Clinical Applications of Artificial Intelligence and Machine Learning in Cardiac Anesthesiology.

Journal of cardiothoracic and vascular anesthesia
Artificial intelligence- (AI) and machine learning (ML)-based applications are becoming increasingly pervasive in the healthcare setting. This has in turn challenged clinicians, hospital administrators, and health policymakers to understand such tech...

Automated inversion time selection for late gadolinium-enhanced cardiac magnetic resonance imaging.

European radiology
OBJECTIVES: To develop and share a deep learning method that can accurately identify optimal inversion time (TI) from multi-vendor, multi-institutional and multi-field strength inversion scout (TI scout) sequences for late gadolinium enhancement card...

An Anatomy- and Topology-Preserving Framework for Coronary Artery Segmentation.

IEEE transactions on medical imaging
Coronary artery segmentation is critical for coronary artery disease diagnosis but challenging due to its tortuous course with numerous small branches and inter-subject variations. Most existing studies ignore important anatomical information and vas...

Value Creation Through Artificial Intelligence and Cardiovascular Imaging: A Scientific Statement From the American Heart Association.

Circulation
Multiple applications for machine learning and artificial intelligence (AI) in cardiovascular imaging are being proposed and developed. However, the processes involved in implementing AI in cardiovascular imaging are highly diverse, varying by imagin...