FDA Radiology AI Devices

The Dreem 3S is a wearable headband device that uses EEG electrodes and a 3D accelerometer to record brain electrical activity and movement during sleep. It applies an artificial neural network to automatically analyze and classify sleep stages, providing clinicians with detailed reports of patients' sleep patterns to aid in sleep assessment at home or in healthcare settings.

Spine Planning 2.0 is a software tool that helps surgeons plan spinal surgeries using medical images like CT, MR, and X-rays. It uses AI to automatically label vertebrae and suggest spinal implants such as screws and rods, improving accuracy and efficiency during preoperative and intraoperative planning.

The Global Hypoperfusion Index (GHI) Algorithm is a software tool used on compatible advanced monitoring platforms to predict the risk of a global hypoperfusion event in surgical or non-surgical patients. It analyzes physiological data to provide clinicians with early warning of potential hemodynamic instability, helping to anticipate and manage patient deterioration in critical care settings.

ME-APDS (Magentiq Eye’s Automatic Polyp Detection System) is an AI-powered software system that assists endoscopists during colonoscopy by automatically detecting and highlighting polyps and other mucosal abnormalities in real-time video images captured by standard white-light endoscopy. It runs on video output from standard colonoscopy equipment to enhance lesion detection, improving the accuracy and efficiency of colorectal screening and surveillance. It helps clinicians by providing visual prompts of suspected polyps, enabling timely clinical actions while functioning as an adjunct tool.

The Cranial Navigation and Cranial EM System by Brainlab AG is an image-guided surgical navigation system designed to assist surgeons during cranial and craniofacial procedures. It uses imaging data like CT, MR, X-Ray, and ultrasound to track surgical instruments relative to patient anatomy. The system integrates artificial intelligence via machine learning algorithms to detect brain abnormalities and anatomical landmarks in MR images to enhance registration accuracy and view centering, helping surgeons perform more precise navigation in complex brain surgeries.

uOmnispace is a medical image post-processing software solution that supports viewing, manipulation, annotation, and communication of various medical images from multiple modalities including CT, MRI, PET and DR. It includes AI-based segmentation tools like rib segmentation, and enables remote multi-user access and integration with medical imaging systems. It helps clinicians efficiently analyze and report on diagnostic images.

Brainlab Elements is a suite of software applications that process and analyze medical image data from various modalities to assist clinicians in planning surgeries and radiation treatments. It offers tools for image registration (fusion), segmentation (contouring), diffusion tensor imaging (fibertracking), blood oxygen level dependent MRI analysis (BOLD MRI mapping), and cerebrovascular image fusion (Image Fusion Angio). These capabilities help improve precision and understanding of patient anatomy and function during clinical procedures.

The Biograph Vision.X and Biograph Vision.X Edge are advanced combined PET and CT scanners that provide high-resolution images by fusing metabolic and anatomical information. These systems assist healthcare professionals in detecting, diagnosing, and monitoring diseases such as cancer, cardiovascular and neurological disorders, and support treatment planning and interventional procedures.

AusculThing ACC is an AI-powered decision support software that analyzes heart sounds recorded by an electronic stethoscope to help healthcare providers distinguish between normal and abnormal heart murmurs. It provides instant, automated analysis and visual and acoustic feedback to support clinical evaluation in both adult and pediatric patients.

EyeArt v2.2.0 is an AI-based software device designed to automatically detect more than mild and vision-threatening diabetic retinopathy in retinal fundus images. It assists healthcare providers by analyzing images captured from specific retinal cameras and providing diagnostic screening results to help identify retinal disease in adults with diabetes, facilitating early detection and treatment.