FDA Radiology AI Devices

The Ultrasound Imaging System (LU700, 128, and LX Series) by Leltek Inc. is a portable, software-controlled ultrasound system that runs on commercial mobile devices. It uses wireless transducers communicating over Wi-Fi to acquire and display real-time, high-resolution ultrasound images across multiple modes such as B-mode and Doppler modes. It aids clinicians in evaluating various body regions and conditions by providing versatile imaging capabilities tailored for different probes and clinical applications.

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.

The !M1 mobile X-ray system by Solutions for tomorrow AB is a diagnostic mobile X-ray system designed to perform general radiography exams on pediatric and adult patients in healthcare facilities. It utilizes digital radiography technology with flat-panel detectors, offering configurations with detectors from manufacturers like Canon, Konica Minolta, and Vieworks, improving image quality and system performance. This helps clinicians obtain diagnostic images efficiently both inside and outside standard X-ray rooms, improving patient care.

ANKYRAS is a medical software device designed to assist clinicians in visualizing cerebral blood vessels and simulating the placement and sizing of neurointerventional braided endovascular devices such as flow diverters. It helps physicians plan neurovascular interventions by allowing 3D modeling based on imaging data from 3D rotational angiography, offering features like segmentation, centerline generation, and device simulation to improve pre-surgical planning and patient outcomes.

Second Opinion® Pediatric is an AI-driven software designed to assist dental clinicians in detecting caries in bitewing and periapical radiographs of patients aged 4 years and older. It uses machine learning to identify and visually overlay potential caries lesions on dental X-rays, helping clinicians with improved detection accuracy without replacing professional judgment.

AeviceMD is a wearable, non-invasive electronic stethoscope that records lung sounds from pediatric patients. It stores these sound recordings securely on a cloud platform, allowing healthcare professionals to later review, compare, and analyze them to support clinical assessments. The system includes hardware sensors, docking station, mobile and web apps, and cloud analytics to facilitate longitudinal monitoring of lung sound data.

The Arthrex Synergy Vision Endoscopic Imaging System is an advanced camera system used in endoscopic surgery to provide live imaging in visible and near-infrared light. It helps surgeons visualize vessels, blood flow, lymphatic system, and tissues during minimally invasive surgeries, improving surgical precision and patient outcomes.

The CIONIC Neural Sleeve NS-200 is a wearable device that helps adults with foot drop and muscle weakness by electrically stimulating specific leg muscles to assist ankle and knee movements. It includes sensors to measure muscle activity, providing real-time biofeedback to guide stimulation and rehabilitation. It aims to improve gait, facilitate muscle re-education, prevent atrophy, and increase blood flow.

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.