AIMC Topic: Echocardiography

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Use of artificial intelligence-guided echocardiography to detect cardiac dysfunction and heart valve disease in rural and remote areas: Rationale and design of the AGILE-echo trial.

American heart journal Aug 10, 2024
BACKGROUND: Transthoracic echocardiography (TTE) is essential in the diagnosis of cardiovascular diseases (CVD), including but not limited to heart failure (HF) and heart valve disease (HVD). However, its dependence on expert acquisition means that i...
Aged Male Echocardiography Middle Aged Rural Population Australia Heart Failure Heart Valve Diseases Humans Artificial Intelligence Female
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Assessment of left ventricular wall thickness and dimension: accuracy of a deep learning model with prediction uncertainty.

The international journal of cardiovascular imaging Aug 10, 2024
Left ventricular (LV) geometric patterns aid clinicians in the diagnosis and prognostication of various cardiomyopathies. The aim of this study is to assess the accuracy and reproducibility of LV dimensions and wall thickness using deep learning (DL)...
Aged Male Ventricular Function, Left Echocardiography Humans Female Reproducibility of Results Heart Ventricles Image Interpretation, Computer-Assisted Models, Cardiovascular Uncertainty Middle Aged Deep Learning Predictive Value of Tests Anatomic Landmarks
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Development of an artificial intelligence-based algorithm for predicting the severity of myxomatous mitral valve disease from thoracic radiographs by using two grading systems.

Research in veterinary science Aug 8, 2024
A heart-convolutional neural network (heart-CNN) was designed and tested for the automatic classification of chest radiographs in dogs affected by myxomatous mitral valve disease (MMVD) at different stages of disease severity. A retrospective and mul...
Neural Networks, Computer Animals Male Echocardiography Severity of Illness Index Artificial Intelligence Algorithms Retrospective Studies Female Radiography, Thoracic Dogs Dog Diseases Mitral Valve Insufficiency
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A YOLOX-Based Deep Instance Segmentation Neural Network for Cardiac Anatomical Structures in Fetal Ultrasound Images.

IEEE/ACM transactions on computational biology and bioinformatics Aug 8, 2024
Echocardiography is an essential procedure for the prenatal examination of the fetus for congenital heart disease (CHD). Accurate segmentation of key anatomical structures in a four-chamber view is an essential step in measuring fetal growth paramete...
Image Interpretation, Computer-Assisted Heart Defects, Congenital Fetal Heart Echocardiography Ultrasonography, Prenatal Deep Learning Humans Neural Networks, Computer Algorithms Pregnancy Female
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Transforming Echocardiography: The Role of Artificial Intelligence in Enhancing Diagnostic Accuracy and Accessibility.

Internal medicine (Tokyo, Japan) Jul 25, 2024
Artificial intelligence (AI) has shown transformative potential in various medical fields, including diagnostic imaging. Recent advances in AI-driven technologies have opened new avenues for improving echocardiographic practices. AI algorithms enhanc...
Echocardiography Health Services Accessibility Japan Telemedicine Humans Artificial Intelligence Cardiovascular Diseases
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Artificial intelligence-derived left ventricular strain in echocardiography in patients treated with chemotherapy.

The international journal of cardiovascular imaging Jul 23, 2024
Global longitudinal strain (GLS) is an echocardiographic measure to detect chemotherapy-related cardiovascular dysfunction. However, its limited availability and the needed expertise may restrict its generalization. Artificial intelligence (AI)-based...
Middle Aged Humans Ventricular Function, Left Observer Variation Neoplasms Reproducibility of Results Stroke Volume Artificial Intelligence Cardiotoxicity Heart Ventricles Antineoplastic Agents Echocardiography Aged Retrospective Studies Ventricular Remodeling Predictive Value of Tests Aged, 80 and over Female Ventricular Dysfunction, Left Male Image Interpretation, Computer-Assisted
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A spatio-temporal graph convolutional network for ultrasound echocardiographic landmark detection.

Medical image analysis Jul 10, 2024
Landmark detection is a crucial task in medical image analysis, with applications across various fields. However, current methods struggle to accurately locate landmarks in medical images with blurred tissue boundaries due to low image quality. In pa...
Image Processing, Computer-Assisted Anatomic Landmarks Heart Ventricles Algorithms Humans Echocardiography Neural Networks, Computer Spatio-Temporal Analysis
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Automated Quality Assessment of Medical Images in Echocardiography Using Neural Networks with Adaptive Ranking and Structure-Aware Learning.

International journal of neural systems Jul 10, 2024
The quality of medical images is crucial for accurately diagnosing and treating various diseases. However, current automated methods for assessing image quality are based on neural networks, which often focus solely on pixel distortion and overlook t...
Humans Neural Networks, Computer Machine Learning Echocardiography Image Processing, Computer-Assisted
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2-Dimensional Echocardiographic Global Longitudinal Strain With Artificial Intelligence Using Open Data From a UK-Wide Collaborative.

JACC. Cardiovascular imaging Jul 10, 2024
BACKGROUND: Global longitudinal strain (GLS) is reported to be more reproducible and prognostic than ejection fraction. Automated, transparent methods may increase trust and uptake.
Neural Networks, Computer Machine Learning Reproducibility of Results Biomechanical Phenomena Ventricular Function, Left Echocardiography Consensus Observer Variation Humans Ventricular Dysfunction, Left Predictive Value of Tests United Kingdom Image Interpretation, Computer-Assisted Myocardial Contraction Datasets as Topic Global Longitudinal Strain
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Multicenter validation study for automated left ventricular ejection fraction assessment using a handheld ultrasound with artificial intelligence.

Scientific reports Jul 4, 2024
We sought to validate the ability of a novel handheld ultrasound device with an artificial intelligence program (AI-POCUS) that automatically assesses left ventricular ejection fraction (LVEF). AI-POCUS was used to prospectively scan 200 patients in ...
Ultrasonography Heart Ventricles Ventricular Dysfunction, Left Humans Ventricular Function, Left Artificial Intelligence Stroke Volume Prospective Studies Female Echocardiography Aged Middle Aged Male
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