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Echocardiography

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Deep Learning-Derived Myocardial Strain.

JACC. Cardiovascular imaging
BACKGROUND: Echocardiographic strain measurements require extensive operator experience and have significant intervendor variability. Creating an automated, open-source, vendor-agnostic method to retrospectively measure global longitudinal strain (GL...

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...

US2Mask: Image-to-mask generation learning via a conditional GAN for cardiac ultrasound image segmentation.

Computers in biology and medicine
Cardiac ultrasound (US) image segmentation is vital for evaluating clinical indices, but it often demands a large dataset and expert annotations, resulting in high costs for deep learning algorithms. To address this, our study presents a framework ut...

An Automated Heart Shunt Recognition Pipeline Using Deep Neural Networks.

Journal of imaging informatics in medicine
Automated recognition of heart shunts using saline contrast transthoracic echocardiography (SC-TTE) has the potential to transform clinical practice, enabling non-experts to assess heart shunt lesions. This study aims to develop a fully automated and...

Automated echocardiographic left ventricular dimension assessment in dogs using artificial intelligence: Development and validation.

Journal of veterinary internal medicine
BACKGROUND: Artificial intelligence (AI) could improve accuracy and reproducibility of echocardiographic measurements in dogs.

Atrial Septal Defect Detection in Children Based on Ultrasound Video Using Multiple Instances Learning.

Journal of imaging informatics in medicine
Thoracic echocardiography (TTE) can provide sufficient cardiac structure information, evaluate hemodynamics and cardiac function, and is an effective method for atrial septal defect (ASD) examination. This paper aims to study a deep learning method b...

Mitral Valve Segmentation and Tracking from Transthoracic Echocardiography Using Deep Learning.

Ultrasound in medicine & biology
OBJECTIVE: Valvular heart diseases (VHDs) pose a significant public health burden, and deciding the best treatment strategy necessitates accurate assessment of heart valve function. Transthoracic echocardiography (TTE) is the key modality to evaluate...

Pragmatic Evaluation of a Deep-Learning Algorithm to Automate Ejection Fraction on Hand-Held, Point-of-Care Echocardiography in a Cardiac Surgical Operating Room.

Journal of cardiothoracic and vascular anesthesia
OBJECTIVE: To test the correlation of ejection fraction (EF) estimated by a deep-learning-based, automated algorithm (Auto EF) versus an EF estimated by Simpson's method.

Advances in the Application of Artificial Intelligence in Fetal Echocardiography.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Congenital heart disease is a severe health risk for newborns. Early detection of abnormalities in fetal cardiac structure and function during pregnancy can help patients seek timely diagnostic and therapeutic advice, and early intervention planning ...