FDA Radiology AI Devices

EnsoSleep is a software tool that uses AI algorithms to analyze sleep study data, including brain waves and breathing patterns, to help physicians evaluate sleep quality and diagnose sleep-related disorders such as sleep apnea. It automates scoring of sleep stages, detection of arousals, leg movements, and breathing events, improving efficiency while requiring clinician verification.

ClearRead CT is a software application that helps radiologists detect lung nodules in chest CT scans by providing enhanced image processing with vessel suppression and computer-aided marking. This assists radiologists in identifying potential nodules more effectively and efficiently during their review, improving diagnostic accuracy and workflow.

The Triton System is a medical software application designed to assist surgical teams by estimating the amount of blood loss on used surgical sponges through image analysis. It runs on an iPad and uses validated hardware and software to calculate hemoglobin mass and blood volume, helping clinicians manage bleeding and surgical sponges more effectively during operations.

HeartFlow FFRct is a software tool that analyzes existing CT images of coronary arteries to calculate fractional flow reserve (FFRCT). This helps clinicians assess the functional significance of coronary artery disease non-invasively, aiding diagnosis and treatment decisions without requiring additional imaging or radiation.

The Personalized Physiology Analytics Engine software is a computerized analysis tool designed to monitor changes in a patient's vital signs relationships over time. Using data such as heart rate, respiratory rate, and activity, it calculates a Multivariate Change Index that helps clinicians track significant physiological changes during routine monitoring, aiding in patient assessment but not for direct diagnostic decisions.

DeltaView Model 2.1 is a software tool that processes current and prior chest x-ray images of the same patient to create a difference image highlighting areas of change. This assists radiologists in detecting lung nodules that have changed over time, improving diagnostic accuracy without replacing the original x-ray images.