The Caption Interpretation Automated Ejection Fraction Software uses AI to analyze transthoracic cardiac ultrasound images and automatically estimate the left ventricular ejection fraction. This helps clinicians in cardiac evaluations by providing a consistent and efficient measurement of heart function, aiding diagnosis and treatment decisions.
LVivo Software Application is an AI-powered ultrasound image analysis platform that automatically calculates important medical parameters related to cardiac and bladder function. It helps clinicians assess heart ventricles and bladder volume using processed ultrasound images, thereby improving diagnostic efficiency and accuracy.
MEDO ARIA is a cloud-based medical imaging software that uses machine learning to help clinicians view, quantify, and generate reports from ultrasound images of infant hips. It supports diagnosis of developmental hip dysplasia (DDH) in newborns and infants up to 12 months, assisting radiologists by automating some image analysis tasks and improving workflow efficiency.
QLAB Advanced Quantification Software is a software application that assists clinicians by providing advanced tools to view and quantify ultrasound image data, specifically for cardiac assessment including mitral valve quantification, helping improve diagnosis and treatment planning.
QLAB Advanced Quantification Software is a tool designed to help clinicians view and measure ultrasound images, specifically focusing on analyzing the heart's right ventricle using advanced automatic segmentation and machine learning. It assists healthcare professionals by providing accurate measurements that improve cardiac assessments without manual contouring for most cases, making the diagnostic process faster and more reliable.
EchoGo Core is an automated software application that processes echocardiogram images to measure cardiac function parameters such as ejection fraction, global longitudinal strain, and left ventricular volumes. It provides clinicians with quantitative reports to assist in diagnosing heart conditions, improving accuracy and reducing variability compared to manual methods.
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