FDA Radiology AI Devices

SwiftMR is a software device that automatically enhances MRI images by reducing noise and increasing image sharpness using deep learning algorithms. It supports brain, spine, and musculoskeletal MRI images and integrates with existing PACS systems to improve diagnostic image quality without interrupting clinical workflow.

The syngo.CT CaScoring software by Siemens is used to analyze non-contrast cardiac CT scans to detect and evaluate calcified lesions in coronary arteries. It calculates scores like the Agatston score, mass, and volume scores for different coronary arteries, helping physicians assess coronary artery disease and generate detailed reports to support patient management.

BriefCase by Aidoc Medical is an AI-powered software that analyzes non-enhanced head CT images to identify potential intracranial hemorrhage. It assists clinicians by flagging suspect cases and sending notifications with preview images to help prioritize patient care workflow. It operates alongside standard imaging interpretation without altering original medical images.

Rapid PE Triage and Notification (PETN) is an AI-powered software that analyzes CT pulmonary angiography scans to detect and notify clinicians of suspected central pulmonary embolism cases. It assists hospital networks and clinicians by prioritizing patient workflows and flagging positive findings, helping improve timely diagnosis and treatment without altering original medical images.

The Achieva, Ingenia, Ingenia CX, Ingenia Elition and Ingenia Ambition MR Systems by Philips are advanced 1.5 and 3.0 Tesla MRI machines that produce high-quality cross-sectional images to help physicians diagnose various conditions. They include AI-enhanced features like SmartSpeed AI for faster image acquisition without loss of quality, aiding clinicians with quicker and improved diagnostic imaging.

Quantib Prostate is an AI-powered image post-processing software designed to assist medical professionals in analyzing prostate MRI scans. It provides tools for visualization, semi-automatic segmentation of prostate anatomy and lesions, volume computations, and PI-RADS scoring support to facilitate the interpretation of prostate MR studies, aiding clinical decision-making.

MAGNETOM Skyra Fit is a 3 Tesla MRI system by Siemens designed to produce detailed transverse, sagittal, coronal, and oblique cross-sectional magnetic resonance images and spectra of the head, body, and extremities. It assists clinicians by providing high-quality images and physical parameters helpful for diagnosis, and can also support imaging during interventional procedures.

Saige-Dx is an AI-based software that analyzes digital breast tomosynthesis mammograms to detect suspicious soft tissue lesions and calcifications that may indicate cancer. It provides radiologists with a suspicion level for each finding and the entire case, helping improve detection accuracy and reduce reading time during breast cancer screening.

The Versana Balance by GE Medical Systems is a general-purpose diagnostic ultrasound system intended for use by trained healthcare professionals. It offers various imaging modes including B-mode, Doppler, 3D/4D imaging, and elastography. The device assists clinicians by providing high-quality ultrasound images and includes AI features such as Whizz Label for anatomy identification, helping in image interpretation and workflow efficiency. It is designed for use in hospitals and clinics across a broad range of clinical applications including abdominal, cardiac, obstetrics, gynecology, vascular and musculoskeletal imaging.

Overjet Caries Assist is an AI-powered software that helps dentists detect and outline tooth decay on bitewing dental X-ray images. It automatically identifies possible caries areas, providing visual annotations to assist dentists in diagnosis and treatment planning. This tool supports dental professionals by improving caries detection sensitivity while allowing them to review and adjust annotations, enhancing diagnostic accuracy without replacing clinical judgment.