FDA Radiology AI Devices

EchoGo Heart Failure 2.0 is an AI-powered software tool that analyzes echocardiogram images of the heart's apical four-chamber view to support clinicians in detecting heart failure with preserved ejection fraction (HFpEF). It provides a diagnostic aid by outputting a classification and a confidence score, enhancing cardiovascular assessments and helping guide clinical decision-making.

FETOLY-HEART is a software tool that helps healthcare professionals during fetal ultrasound exams by automatically detecting key fetal heart views and assessing the quality of those views in real-time. It supports clinicians in ensuring a complete and accurate fetal heart examination, particularly in the second and third trimesters of pregnancy, improving diagnostic confidence and workflow efficiency.

ADAS 3D is an AI-powered software tool that processes cardiac MRI and CT images to support visualization, quantification, and analysis of heart structures and myocardial fibrosis in patients with cardiovascular disease. It aids medical professionals in making informed decisions for cardiac care by providing detailed 3D imaging data, especially for pre-planning and during electrophysiology procedures.

Imbio PHA (4.0.0) is a medical image processing software designed to measure the maximal diameters of the heart's right and left ventricles, the main pulmonary artery, and the ascending aorta from CT pulmonary angiography scans. It uses artificial intelligence to identify and measure these structures, providing annotated images and summary reports to assist clinicians in evaluating cardiovascular health.

HealthCCSng is a software tool that uses artificial intelligence to automatically detect and measure calcified plaques in the coronary arteries from routine non-gated, non-contrast CT scans. It provides an exact calcium score and categorizes the amount of calcium present, with results integrated into the radiologist's workflow to assist in assessing risk for coronary artery disease.

HeartKey Rhythm is a software platform designed to analyze ECG data from various ambulatory monitoring devices such as Holters and ECG patches. Using a combination of machine learning and signal processing, the software detects heartbeats, assesses rhythm, and identifies arrhythmias to assist healthcare professionals in diagnosing cardiac conditions. It integrates through an API into other ECG management or monitoring systems and supports non-urgent clinical decision making.

AI Platform 2.0 (AIP002) by Exo Imaging is an AI-powered software tool designed to assist healthcare professionals by analyzing ultrasound images of the heart and lungs. It helps detect lung structures and artifacts, and quantifies cardiac functions such as left ventricular ejection fraction and myocardium wall thickness. The tool also provides real-time quality feedback to improve ultrasound image acquisition, aiding clinicians in making better diagnostic assessments for adult patients.

AISAP Cardio V1.0 is an AI-powered software that analyzes cardiac point-of-care ultrasound images to detect and assess valvular pathologies like regurgitations and stenosis, and measures key cardiac functions such as ejection fraction and chamber sizes. It supports physicians by generating diagnostic reports that aid in interpreting ultrasound images, improving accuracy and efficiency in evaluating heart conditions in adult patients.

CardIQ Suite is a non-invasive software tool that analyses 2D and 3D CT cardiac images to assist clinicians in visualizing and measuring heart structures and vessels. It provides calcium scoring to evaluate calcified plaques and uses deep learning algorithms to automate segmentation and labeling of heart and coronary arteries, improving diagnostic workflow for cardiovascular diseases.

Tempus ECG-AF is an AI-powered software that analyzes standard 12-lead ECG recordings from patients aged 65 and older to detect signs indicating an increased risk of atrial fibrillation or atrial flutter within the next 12 months. It assists clinicians by providing risk notifications based on ECG data, improving early identification of patients who may require further diagnostic follow-up.