FDA Radiology AI Devices

The VeriSight Intracardiac Echocardiography Catheters (VSICE2D and VSICE3D) are disposable devices used during cardiac procedures to provide real-time ultrasound imaging inside the heart and nearby vessels. They help clinicians visualize cardiac anatomy and physiology in both adult and pediatric patients for guidance during interventions, improving the accuracy and safety of heart treatments.

BrightHeart View Classifier is an AI-powered software that automatically analyzes fetal ultrasound images and video clips to identify standard views of the fetal heart during scans. It helps healthcare professionals by improving the acquisition and interpretation of fetal heart ultrasound exams, making fetal heart imaging more efficient and consistent.

Fetal EchoScan (v1.1) is an AI-driven software device that assists physicians in interpreting second-trimester fetal heart ultrasound videos. It detects suspicious morphological features indicative of congenital heart defects, helping clinicians identify potential heart abnormalities in unborn babies during routine ultrasound exams. The software acts as a concurrent reading aid, providing annotative outputs to improve diagnostic accuracy and support clinical decision-making for fetal cardiac assessment.

The AT-Patch (ATP-C130/ATP-C70) is a wearable ECG monitoring device that records cardiac electrical activity for up to 14 or 7 days respectively. It collects ECG data from a patch worn on the patient's torso, which is then analyzed by software algorithms to detect arrhythmias and other cardiac events. A physician reviews this analysis to provide a report to help clinicians diagnose heart conditions, aiding in the management of symptoms like palpitations, dizziness, and fatigue.

The UltraExtend NX CUW-U001S V2.0 Ultrasound Image Analysis Program by Canon Medical Systems Corporation is software designed to help physicians analyze and observe images from ultrasound examinations. It supports data from specific diagnostic ultrasound systems and includes AI-enabled features for advanced cardiac motion tracking and measurement, aiding clinical decision-making in hospital and clinical settings.

VitalRhythm is a cloud-based AI software that continuously analyzes ECG signals to detect various cardiac arrhythmias. It works with a wearable biosensor (VitalPatch) and displays results to healthcare professionals for non-urgent clinical decision-making in outpatient and non-critical care settings. It helps clinicians monitor heart rhythms remotely and efficiently, assisting in diagnosis without replacing clinical judgment.

LARALAB is an AI-powered medical imaging software that helps cardiologists, radiologists, and heart surgeons visualize, assess, and measure cardiovascular structures from medical images. It automates segmentation and measurements to assist in preprocedural planning and postprocedural review, improving workflow efficiency and accuracy in cardiovascular care.

Vitrea CT VScore is a software application designed to aid medical professionals in visualizing, segmenting, and quantifying calcified lesions in ECG-gated cardiac CT images of patients aged 30 years or older. It provides calcium scoring and generates detailed reports to assist clinicians in cardiac imaging assessment.

QFR (3.0) is a software device that processes X-ray angiogram images to provide quantitative analysis of coronary vessels. It uses deep learning and 3D reconstruction from angiographic images to measure vessel dimensions and quantify pressure drops, aiding cardiologists in evaluating coronary artery disease and supporting treatment decisions.

The WHOOP ECG (electrocardiogram) Feature is a mobile application software used with the WHOOP Strap wearable device to record and analyze a single-channel ECG signal similar to a Lead I ECG. It helps users detect atrial fibrillation, normal sinus rhythm, and abnormal heart rates by providing informational ECG data and rhythm classification, aiding users and clinicians in heart rhythm monitoring without replacing traditional diagnosis methods.