FDA Radiology AI Devices

qXR-BT by Qure.ai Technologies is an AI-powered software designed to analyze chest X-ray images to help physicians confirm the position of breathing tubes. It generates secondary digital images with highlighted tube tips and anatomical landmarks, providing valuable adjunctive information during radiological assessment.

BU-CAD is a software application designed to assist physicians by analyzing breast ultrasound images to identify and evaluate soft tissue lesions suspicious for breast cancer. It highlights regions of interest and provides malignancy scores and BI-RADS classifications to support clinical decision-making. It also supports viewing of mammography images and includes tools for image adjustment and documentation, helping improve diagnostic accuracy and efficiency.

EchoGo Core (2.0) is an AI-powered software that analyzes ultrasound images of the heart (echocardiograms) to automatically quantify and report cardiac function metrics. It assists physicians by providing measurements like ejection fraction, ventricular volume, and strain, helping in cardiovascular diagnosis for adult patients.

MammoScreen 2.0 is an AI-based software tool designed to assist physicians by automatically analyzing standard screening mammograms including FFDM and DBT images. It marks suspicious soft tissue lesions or calcifications on breast images and provides a level of suspicion score to help radiologists improve detection and characterization of breast cancer findings. This tool acts as a concurrent reading aid to improve diagnostic accuracy but does not replace physician judgment.

EndoScreener is a computer-assisted detection software that automatically identifies and highlights potential polyps during colonoscopy procedures. It processes the live video feed from the colonoscope and overlays blue boxes on suspected polyps, alerting the physician in real-time to improve polyp detection and assist clinical decision-making during colonoscopy in adults.

Soteria.AI is an image-intensified fluoroscopic x-ray system designed for use in a variety of radiographic and fluoroscopic applications including cardiac, vascular, general diagnostic, and interventional imaging. It helps reduce patient and operator radiation exposure by automatically providing a region of interest using AI technology, thereby improving safety during imaging procedures.

Lunit INSIGHT MMG is an AI-powered computer-assisted detection and diagnosis software designed to help radiologists detect, localize, and characterize suspicious areas for breast cancer on mammograms. It works as an adjunct tool viewed after the initial physician read, providing visual marks and scores indicating the likelihood of malignancy to assist clinical decision-making and improve breast cancer detection during mammography screenings.

The TEX20 and TEX10 series Diagnostic Ultrasound Systems by Shenzhen Mindray are versatile, software-controlled ultrasound machines designed for imaging adults, pregnant women, pediatric patients, and neonates. They support multiple imaging modes such as B-mode, Doppler (including Color, Power, Pulsed Wave), 3D imaging, elastography, and contrast imaging, helping clinicians visualize and measure anatomical structures and blood flow across a wide range of body areas including ophthalmic, fetal, abdominal, cardiac, and musculoskeletal exams. These systems enhance diagnostic confidence and efficiency for healthcare providers through advanced imaging features and AI-assisted tools such as Smart Nerve, which assists in visualizing nerve plexuses for guidance.

Critical Care Suite with Endotracheal Tube Positioning AI Algorithm is a software tool that uses AI to automatically analyze frontal chest X-rays. It detects and localizes the position of an endotracheal tube and calculates the distance between the tube tip and the carina, providing clinicians with important information on tube placement to improve patient care.

The Irregular Rhythm Notification Feature 2.0 (IRNF 2.0) is a software application used on Apple Watch and iPhone that analyzes pulse rate data using machine learning to detect irregular heart rhythms, such as atrial fibrillation (AFib). It notifies users of possible AFib episodes to help prompt medical consultation, supporting non-invasive heart rhythm monitoring through wearable technology.