FDA Radiology AI Devices

StrokeSENS LVO is software that uses AI to analyze CT angiograms of the head to identify suspected large vessel occlusions, which can cause strokes. It assists healthcare providers by flagging potential LVO cases and sending notifications to specialists in near real-time, helping prioritize urgent cases and improve workflow efficiency. The software does not alter the original images and is intended to be used alongside existing diagnostic workflows.

Deep Learning Image Reconstruction by GE Healthcare is a software that uses deep neural networks to reconstruct high-quality CT images from X-ray transmission data. It helps radiologists by producing images with improved noise reduction, spatial resolution, and artifact suppression, suitable for head, whole body, cardiac, and vascular CT scans at routine clinical throughput.

HealthCCSng is a software device that automatically analyzes non-cardiac-gated CT scans to estimate the amount of calcified plaque in coronary arteries, which can indicate coronary artery disease risk. It provides radiologists with calcium detection categories and annotated images to aid in clinical decision-making within their usual workflow.

The Aquilion Exceed LB is a whole-body multi-slice helical CT scanner that captures detailed cross-sectional images of the body, including the head. It incorporates AiCE, an AI-based noise reduction algorithm using deep convolutional neural networks, to improve image quality and reduce noise. This helps clinicians obtain clearer, more accurate diagnostic images for various body regions, including abdomen, pelvis, lung, cardiac, extremities, head, and inner ear.

AI Segmentation is a cloud-based software product that uses artificial intelligence to automatically segment anatomical structures from CT images. It is designed to assist medical professionals in radiation therapy treatment planning by providing automated contours of organs in regions such as the head and neck, thorax, pelvis, and abdomen. The segmented structures can be reviewed, edited, and approved by qualified treatment planners and physicians to streamline planning and improve accuracy.

InferRead CT Stroke.AI is an AI-powered software that helps hospitals and radiologists prioritize head CT scans by flagging suspected intracranial hemorrhage cases. It analyzes CT images using a deep learning algorithm and highlights potential emergency cases on a worklist, assisting clinicians in faster triage. The software operates alongside standard radiology workflows without altering images or removing cases, improving efficiency in detecting brain hemorrhages.

The uCT ATLAS with uWS-CT-Dual Energy Analysis is a multi-slice CT scanner designed for producing cross-sectional images of the whole body and specific organs using advanced imaging technology. It features fast scanning with high spatial and temporal resolution, low radiation dose, and AI-based enhancements for image quality and patient positioning. Its dual energy analysis software helps differentiate tissue composition using CT images acquired at different energy levels, aiding diagnostic insights.

qER-Quant is an AI-powered software that processes non-contrast head CT scans to automatically identify and quantify key brain structures such as intracranial hyperdensities, lateral ventricles, and midline shift. It helps clinicians by providing volumetric data and visual overlays to aid in diagnosis and monitoring brain conditions over time.

ClariCT.AI is an AI-powered software solution that enhances the quality of CT images by reducing noise, especially in low-dose scans. This helps radiologists get clearer images to improve diagnosis while potentially lowering patient radiation exposure. It is compatible with CT images from any manufacturer and integrates seamlessly with medical IT systems.

HALO is an AI-powered notification software that analyzes brain CT angiograms to detect signs of suspected intracranial Large Vessel Occlusion (LVO). It helps clinicians by promptly notifying appropriate medical specialists to facilitate quicker evaluation and treatment of stroke patients, improving emergency care and patient outcomes.