AIMC Topic: Echocardiography

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Myocardial Function Imaging in Echocardiography Using Deep Learning.

IEEE transactions on medical imaging Apr 30, 2021
Deformation imaging in echocardiography has been shown to have better diagnostic and prognostic value than conventional anatomical measures such as ejection fraction. However, despite clinical availability and demonstrated efficacy, everyday clinical...
Heart Heart Ventricles Motion Humans Echocardiography Deep Learning
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Diagnosing Atrial Septal Defect from Electrocardiogram with Deep Learning.

Pediatric cardiology Apr 27, 2021
The heart murmur associated with atrial septal defects is often faint and can thus only be detected by chance. Although electrocardiogram examination can prompt diagnoses, identification of specific findings remains a major challenge. We demonstrate ...
Retrospective Studies Female Male Humans Neural Networks, Computer Electrocardiography Predictive Value of Tests Heart Septal Defects, Atrial Echocardiography Deep Learning Child
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A deep learning approach for the automatic recognition of prosthetic mitral valve in echocardiographic images.

Computers in biology and medicine Apr 14, 2021
The first step in the automatic evaluation of the cardiac prosthetic valve is the recognition of such valves in echocardiographic images. This research surveyed whether a deep convolutional neural network (DCNN) could improve the recognition of prost...
Deep Learning Humans Echocardiography Mitral Valve Heart Valve Prosthesis
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Multibeat echocardiographic phase detection using deep neural networks.

Computers in biology and medicine Apr 6, 2021
BACKGROUND: Accurate identification of end-diastolic and end-systolic frames in echocardiographic cine loops is important, yet challenging, for human experts. Manual frame selection is subject to uncertainty, affecting crucial clinical measurements, ...
Humans Neural Networks, Computer Echocardiography Observer Variation Diastole
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Echocardiographic image multi-structure segmentation using Cardiac-SegNet.

Medical physics Apr 1, 2021
PURPOSE: Cardiac boundary segmentation of echocardiographic images is important for cardiac function assessment and disease diagnosis. However, it is challenging to segment cardiac ventricles due to the low contrast-to-noise ratio and speckle noise o...
Image Processing, Computer-Assisted Heart Heart Ventricles Neural Networks, Computer Echocardiography Humans
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Deep Learning for Detection of Elevated Pulmonary Artery Wedge Pressure Using Standard Chest X-Ray.

The Canadian journal of cardiology Feb 18, 2021
BACKGROUND: To accurately diagnose and control heart failure (HF), it is important to carry out a simple assessment of elevated pulmonary arterial wedge pressure (PAWP). The aim of this study was to develop and validate an objective method for detect...
Echocardiography Deep Learning Datasets as Topic Natriuretic Peptide, Brain Radiography, Thoracic Pulmonary Wedge Pressure Humans Cardiac Catheterization Female Algorithms Aged Prospective Studies Male
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A deep learning approach with temporal consistency for automatic myocardial segmentation of quantitative myocardial contrast echocardiography.

The international journal of cardiovascular imaging Feb 17, 2021
Quantitative myocardial contrast echocardiography (MCE) has been proved to be valuable in detecting myocardial ischemia. During quantitative MCE analysis, myocardial segmentation is a critical step in determining accurate region of interests (ROIs). ...
Image Processing, Computer-Assisted Predictive Value of Tests Myocardium Neural Networks, Computer Humans Echocardiography Deep Learning
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Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortality.

Nature biomedical engineering Feb 8, 2021
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 longitudinal electronic health records. Here we show that a convolutional neur...
Middle Aged Deep Learning ROC Curve Heart Failure Survival Analysis Image Interpretation, Computer-Assisted Aged Male Echocardiography Electronic Health Records Female Humans Databases, Factual Retrospective Studies
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Harnessing Machine Intelligence in Automatic Echocardiogram Analysis: Current Status, Limitations, and Future Directions.

IEEE reviews in biomedical engineering Jan 22, 2021
Echocardiography (echo) is a critical tool in diagnosing various cardiovascular diseases. Despite its diagnostic and prognostic value, interpretation and analysis of echo images are still widely performed manually by echocardiographers. A plethora of...
Humans Artificial Intelligence Heart Algorithms Image Interpretation, Computer-Assisted Cardiovascular Diseases Echocardiography
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Machine learning methods to improve bedside fluid responsiveness prediction in severe sepsis or septic shock: an observational study.

British journal of anaesthesia Jan 16, 2021
BACKGROUND: Passive leg raising (PLR) predicts fluid responsiveness in critical illness, although restrictions in mobilising patients often preclude this haemodynamic challenge being used. We investigated whether machine learning applied on transthor...
Fluid Therapy Aged Male Point-of-Care Systems Shock, Septic Prospective Studies Echocardiography Humans Predictive Value of Tests Critical Illness Middle Aged Machine Learning Female Sepsis
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